Trending December 2023 # Top 10 Data Science Projects For Final Year Students Of 2023 # Suggested January 2024 # Top 12 Popular

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Data science projects are important for students to sharpen their skills and increase their future possibilities.

For the past few years,

Chatbots

Due to their skillfully handling of a profusion of customer queries and messages without any issue, Chatbots play a significant role for industries. They are designed to lessen the customer service workload by automating the hefty part of the process. Nonetheless,

Fake News Detection

In the list of the top 10 data science projects for the final year students, next is fake news detection. In this tech-driven world, every individual is aware of what fake news exactly is. Sharing fake news over the internet has become one snap thing. You all must have seen misleading information being spread over the internet from unauthorized sources. Such information makes you face issues but, in some circumstances, it has the great potential to cause a huge level of panic and violence. You can create a data science project to stop this spread by choosing Python and developing a model with Passive Aggressive Classifier and Tfid Vectorizer to divide the real news from the fake one.

Forest Fire Prediction

Creating a forest fire prediction system is one of the best data science projects and it will be another considerable utilization of the abilities provided by data science. Forest fire is an uncontrolled fire in a forest causing a hefty amount of damage to not only nature but the animal habitat, and human property as well. To control the chaotic nature of forest fires and even predict them, you can create a data science project utilizing k-means massing to comprehend major fire hotspots and their intensity.

Driver Drowsiness Detection

Every day there is at least one news of a road accident. One of the major reasons for road accidents has been sleepy drivers. To avoid unnecessary deaths and road accidents, datascience students can create a drowsiness detection system. This is yet another data science project that has the great potential to save a profusion of lives by continuously detecting the driver’s eyes and alerting him with alarms in case the system finds often closes of driver’s eyes.

Brain Tumor Detection with Data Science

There are many famous data science projects on MRI scan datasets. One of them is Brain Tumor detection. You can utilize transfer learning on these MRI scans to get the mandatory details for classification. Or you can train your convolution neural network from scratch to detect brain tumors. This is definitely one of the best data science project ideas.

Image Caption Generator Project in Python

This is one of the most interesting data science projects. It is easy for humans to describe what is in an image but for computers, an image is just a bunch of numbers that represent the color value of each pixel. This datascience project utilizes deep learning methods where you implement a convolutional neural network (CNN) with a Recurrent Neural Network (LSTM) to build the image caption generator.

Breast Cancer Classification with Artificial Intelligence and Data Science

Breast Cancer Classification is yet another medical contribution of data science and Artificial Intelligence. For this project, you have to use the IDC_regular dataset to detect the presence of Invasive Ductal Carcinoma, the most common form of breast cancer. It develops in a milk duct invading the fibrous or fatty breast tissue outside the duct. In this data science project idea, you have to utilize Deep Learning and the Keras library for classification.

Traffic Signs Recognition

Traffic signs and rules are crucial that every driver must obey to prevent accidents. To follow the rule, one must first understand how the traffic sign looks like. In the Traffic signs recognition project, you will learn how a program can identify the type of traffic sign by taking an image as input. For a final-year student, it is one of the best data science projects to try.

Customer Segmentation

This is one of the most popular data science projects every student should try. Before running any campaign companies create different groups of customers. Customer segmentation is a popular application of unsupervised learning. Using clustering, companies identify segments of customers to target the potential user base.

Movie Recommendation System

For the past few years, artificial intelligence and data science has been flourishing and the focus on these technologies will take them to heights. Businesses are acknowledging the significance of data science; numerous opportunities are tapping at your door. If you are studying data science and it is your final year, now is the perfect time to start working on your data science project. This article features current ideas for your upcoming data science project. Here is the list of the top 10 data science projects that you should not chúng tôi to their skillfully handling of a profusion of customer queries and messages without any issue, Chatbots play a significant role for industries. They are designed to lessen the customer service workload by automating the hefty part of the process. Nonetheless, chatbots execute this by utilizing their promising methods supported by the technologies like machine learning, artificial intelligence and datascience. Therefore, creating a chatbot for your final data science project will be a great chúng tôi the list of the top 10 data science projects for the final year students, next is fake news detection. In this tech-driven world, every individual is aware of what fake news exactly is. Sharing fake news over the internet has become one snap thing. You all must have seen misleading information being spread over the internet from unauthorized sources. Such information makes you face issues but, in some circumstances, it has the great potential to cause a huge level of panic and violence. You can create a data science project to stop this spread by choosing Python and developing a model with Passive Aggressive Classifier and Tfid Vectorizer to divide the real news from the fake one.Creating a forest fire prediction system is one of the best data science projects and it will be another considerable utilization of the abilities provided by data science. Forest fire is an uncontrolled fire in a forest causing a hefty amount of damage to not only nature but the animal habitat, and human property as well. To control the chaotic nature of forest fires and even predict them, you can create a data science project utilizing k-means massing to comprehend major fire hotspots and their intensity.Every day there is at least one news of a road accident. One of the major reasons for road accidents has been sleepy drivers. To avoid unnecessary deaths and road accidents, datascience students can create a drowsiness detection system. This is yet another data science project that has the great potential to save a profusion of lives by continuously detecting the driver’s eyes and alerting him with alarms in case the system finds often closes of driver’s eyes.There are many famous data science projects on MRI scan datasets. One of them is Brain Tumor detection. You can utilize transfer learning on these MRI scans to get the mandatory details for classification. Or you can train your convolution neural network from scratch to detect brain tumors. This is definitely one of the best data science project chúng tôi is one of the most interesting data science projects. It is easy for humans to describe what is in an image but for computers, an image is just a bunch of numbers that represent the color value of each pixel. This datascience project utilizes deep learning methods where you implement a convolutional neural network (CNN) with a Recurrent Neural Network (LSTM) to build the image caption generator.Breast Cancer Classification is yet another medical contribution of data science and Artificial Intelligence. For this project, you have to use the IDC_regular dataset to detect the presence of Invasive Ductal Carcinoma, the most common form of breast cancer. It develops in a milk duct invading the fibrous or fatty breast tissue outside the duct. In this data science project idea, you have to utilize Deep Learning and the Keras library for classification.Traffic signs and rules are crucial that every driver must obey to prevent accidents. To follow the rule, one must first understand how the traffic sign looks like. In the Traffic signs recognition project, you will learn how a program can identify the type of traffic sign by taking an image as input. For a final-year student, it is one of the best data science projects to chúng tôi is one of the most popular data science projects every student should try. Before running any campaign companies create different groups of customers. Customer segmentation is a popular application of unsupervised learning. Using clustering, companies identify segments of customers to target the potential user chúng tôi this data science project, you have to utilize R to perform a movie recommendation through technologies like Machine Learning and Artificial Intelligence. A recommendation system sends out suggestions to users through a filtering process based on other users’ preferences and browsing history. If A and B like Home Alone and B likes Mean Girls, it can be suggested to A – they might like it too. This keeps customers engaged with the platform.

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Top Data Science Jobs In Gurgaon Available For Data Scientists In 2023

Analytics Insight has churned out the top Data Science jobs in Gurgaon available in 2023 Data Scientist at Airtel

Airtel is known as one of the largest telecom service providers for customers and businesses in India. It also operates in 18 countries with products such as 2G, 3G and 4G wireless services, high-speed home broadband as well as DTH. The company consists of more than 403 million customers across the world. Responsibilities: The data scientist needs to research, design, implement as well as evaluate novel Computer Vision algorithms, work on large-scale datasets and create scalable systems in versatile application fields. The candidate is required to work closely with the customer expertise team, research scientist teams as well as product engineering teams to drive model implementations along with new algorithms. The candidate also needs to interact with the customer to gain a better understanding of the business problems and help them by implementing machine learning solutions. Qualifications: A candidate is required to have practical experience in Computer Vision and more than three years in building production-scale systems in either Computer Vision, deep learning or machine learning. There should be coding skills in one programming language and a clear understanding of deep learning CV evaluation metrics such as mAP, F_beta and PR curves as well as face detection, facial recognition and OCR. The candidate also needs to have 2-3 years of modelling experience working with Pytorch, MxNet and Tensorflow along with object detection approaches such as Faster RCNN, YOLO and CenterNet.

Data Scientist at BluSmart

BluSmart is known as the first and leading all-electric ride-hailing mobility service in India. It has a mission to steer urban India towards a sustainable means of transportation by building a comprehensive electric on-demand mobility platform with smart charging and smart parking. The company will provide efficient, affordable, intelligent as well as reliable mobility. Responsibilities: The candidate is required to do a geospatial and time-based analysis of business vectors like time-travelled, fare, trip start and many more to optimise fleet utilisation and deployment as well as develop strategies to deploy electric vehicles and chargers in Delhi-NCR along with Mumbai by using data from thousands of trip from BluSmart cabs. The data scientist will create a new experimental framework to collect data and build tools to automate data collection by using open-source data analysis and visualisation tools. Qualifications: The candidate is required to have sufficient knowledge of data analytics, machine learning, and programming languages such as R, SQL and Python. The candidate needs to have practical experience with data analytics, machine learning and business intelligence tools such as Tableau with smart mathematical skills.

Associate Data Scientist at Pee Safe

Responsibilities: The data scientist should receive actionable insights from data to be used in real-time in all decision-making processes for the company and implement multiple processes across different departments to enhance business metrics. The candidate needs to create new models or improve existing models to be used for the supply chain, demand predictions, logistics and many more. Qualifications: The candidate should have a Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering or any other relevant field. The candidate is required to have at least two to three years of practical experience in quantitative analytics or data modelling. It is essential to have a clear understanding of predictive modelling, machine learning, clustering, classification techniques, algorithms, programming language as well as Big Data frameworks and visualisation tools such as Cassandra, Hadoop, Spark and Tableau. The candidate must have strong problem-solving skills with sufficient knowledge of Excel.

Data Scientist at Siemens Limited

Siemens is popularly known as a technology company focused on industry, infrastructure, mobility as well as healthcare. It aims in creating technologies for more resource-efficient factories along with resilient supply chains to transform industries. Responsibilities: The candidate is required to design software solutions supplemented with Artificial Intelligence and machine learning based on the customer requirements within architectural or design guidelines. The candidate also needs to be involved in the coding of features, bug fixing as well as delivering solutions to scripting and quality guidelines. The person is responsible for ensuring integration and submission of solutions into software configuration management system, performing regular technical coordination and timely reporting. Qualifications: The candidate must have a strong knowledge of Data Science, Artificial Intelligence, machine learning, deep learning, exploratory analysis, predictive modelling, prescriptive modelling and Cloud systems with a B.E/B. Tech/ CA/ M. Tech in science background. The candidate should have practical experience in data visualisation tools, statistical computer languages, data architecture and machine learning techniques. It is essential to have a good knowledge of querying SQL, no SQL databases, data mining techniques, AWS services, computing tools as well as end-to-end Data Science pipelines into production.

Data Scientist at Mastercard

Mastercard is known as the global technology company in the financial industry, especially payments. It has a mission to connect an inclusive digital economy to benefit everyone by making transactions safe and accessible. It works in more than 210 countries with secure data and networks, innovations and solutions. Qualifications: The candidate should have practical experience in data management, support decks, SQL Server, Microsoft BI Stack, Python, campaign analytics, SSIS, SSAS, SSRS and data visualisation tools. It is essential to have a Bachelor’s or Master’s degree in Computer Science, IT, Engineering, Mathematics, Statistics or any relevant field.

Top 10 Big Data Trends Of 2023

2023 was a major year over the big data landscape. In the wake of beginning the year with the Cloudera and Hortonworks merger, we’ve seen huge upticks in Big Data use across the world, with organizations running to embrace the significance of data operations and orchestration to their business success. The big data industry is presently worth $189 Billion, an expansion of $20 Billion more than 2023, and is set to proceed with its rapid growth and reach $247 Billion by 2023. It’s the ideal opportunity for us to look at Big Data trends for 2023.

Chief Data Officers (CDOs) will be the Center of Attraction

The positions of Data Scientists and Chief Data Officers (CDOs) are modestly new, anyway, the prerequisite for these experts on the work is currently high. As the volume of data continues developing, the requirement for data professionals additionally arrives at a specific limit of business requirements. CDO is a C-level authority at risk for data availability, integrity, and security in a company. As more businessmen comprehend the noteworthiness of this job, enlisting a CDO is transforming into the norm. The prerequisite for these experts will stay to be in big data trends for quite a long time.

Investment in Big Data Analytics

Analytics gives an upper hand to organizations. Gartner is foreseeing that organizations that aren’t putting intensely in analytics by the end of 2023 may not be ready to go in 2023. (It is expected that private ventures, for example, self-employed handymen, gardeners, and many artists, are excluded from this forecast.) The real-time speech analytics market has seen its previously sustained adoption cycle beginning in 2023. The idea of customer journey analytics is anticipated to grow consistently, with the objective of improving enterprise productivity and the client experience. Real-time speech analytics and customer journey analytics will increase its popularity in 2023.

Multi-cloud and Hybrid are Setting Deep Roots

In 2023, we hope to see later adopters arrive at a conclusion of having multi-cloud deployment, bringing the hybrid and multi-cloud philosophy to the front line of data ecosystem strategies.

Actionable Data will Grow

Another development concerning big data trends 2023 recognized to be actionable data for faster processing. This data indicates the missing connection between business prepositions and big data. As it was referred before, big data in itself is futile without assessment since it is unreasonably stunning, multi-organized, and voluminous. As opposed to big data patterns, ordinarily relying upon Hadoop and NoSQL databases to look at data in the clump mode, speedy data mulls over planning continuous streams. Because of this data stream handling, data can be separated immediately, within a brief period in only a single millisecond. This conveys more value to companies that can make business decisions and start processes all the more immediately when data is cleaned up.

Continuous Intelligence

Continuous Intelligence is a framework that has integrated real-time analytics with business operations. It measures recorded and current data to give decision-making automation or decision-making support. Continuous intelligence uses several technologies such as optimization, business rule management, event stream processing, augmented analytics, and machine learning. It suggests activities dependent on both historical and real-time data. Gartner predicts more than

Machine Learning will Continue to be in Focus

ML projects have gotten the most investments in 2023, stood out from all other AI systems joined. Automated ML tools help in making pieces of knowledge that would be difficult to separate by various methods, even by expert analysts. This big data innovation stack gives faster results and lifts both general productivity and response times.

Abandon Hadoop for Spark and Databricks

Since showing up in the market, Hadoop has been criticized by numerous individuals in the network for its multifaceted nature. Spark and managed Spark solutions like Databricks are the “new and glossy” player and have accordingly been picking up a foothold as data science workers consider them to be as an answer to all that they disdain about Hadoop. However, running a Spark or Databricks work in data science sandbox and then promoting it into full production will keep on facing challenges. Data engineers will keep on requiring more fit and finish for Spark with regards to enterprise-class data operations and orchestration. Most importantly there are a ton of options to consider between the two platforms, and companies will benefit themselves from that decision for favored abilities and economic worth.

In-Memory Computing

In-memory innovation is utilized to perform complex data analyses in real time. It permits its clients to work with huge data sets with a lot more prominent agility. In 2023, in-memory computing will pick up fame because of the decreases in expenses of memory.

IoT and Big Data

The function of IoT in healthcare can be seen today, likewise, the innovation joining with gig data is pushing companies to get better outcomes. It is expected that 42% of companies that have IoT solutions in progress or IoT creation in progress are expecting to use digitized portables within the following three years.

Digital Transformation Will Be a Key Component

Top 10 Healthcare Data Science Jobs To Apply For In June

There are many aspiring data scientists looking for healthcare data science jobs to bring their expertise to use

Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data science jobs allow data scientists to analyze data for actionable insights. Data science provides aid to process, manage, analyze, and assimilate the large quantities of fragmented, structured, and unstructured data created by healthcare systems. This data requires effective management and analysis to acquire factual results. Data scientists create statistical, network, path, and big data methodologies for predictive fraud propensity models and use those models to create alerts that help ensure timely responses when unusual data is recognized. There are many aspiring data scientists looking for healthcare data science jobs to bring their expertise to use. This article features the top 10 best healthcare data science jobs to apply for in June 2023.

Senior Data Scientist – UnitedHealth Group

Location: Noida, Uttar Pradesh

Responsibilities:

Apply here to this one of the best data science jobs

Senior Data Scientists – Jorie Healthcare Partners

Location: Noida, Uttar Pradesh

Responsibilities:

Has expertise in implementing complex statistical analyses for data processing, exploration, model building and implementation

Work Individually in the use case building and delivery process

Is able to communicate complex technical concepts to both technical and non-technical audience

Plays a key role in driving ideation around the modeling process and developing models.

Is able to conceptualize and drive re-iteration and fine tuning of models

Apply here for this one of the best healthcare data science jobs

Data Analyst – Aster DM Healthcare

Location: Gurugram, Haryana

Responsibilities:

Finding a meaningful sense of healthcare data using innovative techniques

Talk and interact with different stakeholders to understand their analytical requirement

Develop statistical models by leveraging best-in-class modeling techniques

Primarily responsible for data modeling; secondary responsibility towards problem-solving

Hands-on experience with data preparation and visualization

Willingness to spend the time on data management and cleansing

Apply here for one of the best data science jobs

Clinical Data Analyst – Eli Lilly and Company

Location: Bengaluru, Karnataka

Responsibilities:

Creates reporting and analytics solutions with appropriate oversight that support the quality and timely delivery of clinical data reports and visualizations required per standard and study specific data review plans

Serves as a technical resource to the study teams for data visualization and reporting tool

Awareness of drug development process and data operations required for the reporting of clinical trial data (e.g., data review, study reports, regulatory submissions, safety updates, etc.)

Define, measure and achieve proficiency with new tools/technology and processes applicable to focus areas

Apply here

Senior Data Scientist – GE Healthcare

Location: Karnataka

Responsibilities:

Apply here for one of the best healthcare data science jobs.

Lab Data Analyst – IQVIA

Location: Bengaluru, Karnataka

Responsibilities:

Apply here for this job

Healthcare Data Analyst – SCALABLE SYSTEMS

Location: New Delhi, Delhi

Responsibilities:

Translate highly complex concepts and conclusions in a clear and concise manner in ways that can be understood by a variety of audiences

Lead and own the analysis of highly complex data sources, identifying trends and patterns in data and make recommendations based on analysis results

Perform root cause analysis on complex data anomalies and working closely data stewards to define best practice

Facilitate review sessions with management, business users and other team members

Apply here

Sr. Data Scientist – Zeno Health

Location: Remote

Responsibilities:

Design, develop and manage predictive models to solve inventory management problems and improve user engagement using machine learning

Monitor key product metrics, understanding root causes of changes in metrics

Apply here for this one of the best data science jobs.

Data Scientist: Data analytics and Machine learning – Siemens Healthcare Private Limited

Location: Bengaluru, Karnataka

Responsibilities:

Ability to manipulate and analyze large scale, high-dimensionality data from varying sources

Experience in creating and maintaining knowledge graph data structures for SPECT & PET Scanners

Experience in semantic consistency checking

Ability and experience in data integration

Experience in manipulating unstructured, semi-structured and fully structured datasets

Apply here

Data Analyst – Cardinal Health

Location: Bengaluru, Karnataka

Responsibilities:

Designing and implementing data visualization and user interfaces leveraging tools that connect to GCP cloud tools and services as well as AtScale

Designing and building visualizations in conjunction with machine learning algorithms (process and outputs) and providing visibility to next best actions to take

Apply here

Top 10 Data Science Inventions That Left People In Awe In 2023

Data science has smitten everyone with its capabilities. So much so that today, it is practically not possible to think of leading our lives without data science in place. Today, every sector that one can possibly think of relies on data. No wonder why data science is one of the fastest-growing technologies. With an increase in data dependence, quite evidently, the demand for data scientists soars up. Here, we will talk about top 10 data science inventions that left people in awe in 2023.

Heart Disease Prediction Robot

The number of people suffering from heart ailments are increasing with every passing day. What comes to the rescue is designing a heart disease prediction bot that provides online medical consultation and guidance to patients suffering from heart diseases.

House Price Prediction

Under this data science invention, you will be able to predict the selling price of a new home. The dataset of this project would contain the prices of houses in different areas of the country/city.

Prediction of Stock Prices

No wonder everyone is keen to know how the market would perform. If you want to design a project that predicts the stock prices, there cannot be a better technology to rely on than data science. This data science project stands the potential to monitor and analyse the company performance followed by predicting future prices of various stocks.

Movie Ticket Pricing System Personality Predictor

Yet another challenging yet interesting data science project that make it to the list of top 10 data science inventions that left people in awe in 2023 is that of a personality predictor on the basis of the CV uploaded. With an objective to provide a legally justified and fair CV ranking system, this project stands the potential to make the hiring process a lot more manageable.

Sentiment Analyser

As evident as the name of the project, the objective of this data science invention is to analyse the sentiments of the people behind texts, or a post. With this, the organizations are at a much better position to understand consumer behaviour. Following this, the organizations can take steps to improve their customer service.

Plagiarism Checker

Plagiarism checker has to be one of the most interesting projects. The invention is such that it can detect the similarities in copies of text and detect the percentage of plagiarism. This would be a widely accepted project as plagiarism is a serious issue that needs to be controlled and monitored.

Chatbots

As known to many, chatbots are one among the most relied platforms for enhancing customer experience. Creating a chatbot has a lot to do with artificial intelligence. This is because data science forms its base. You can always start by creating a simple chatbot and customize it the way you want by creating a detailed version of the same.

Recommendation Engines

Recommendation engines have gained huge popularity in streaming sites as well as shopping websites as the main agenda of the same is to tailor the content as per the needs and preferences of different customers. This project customize content on the basis of individual customer preferences and browsing history.

Banking Bot

Top 10 Data Science Jobs To Apply For In Govt Organizations This July

Data science jobs in govt organizations are in huge demand similar to private ones in 2023 Top ten data science jobs in government organizations in July 2023 Data designer at NABARD

Location: n/a

Responsibilities: The data designer needs to analyze data needs while using skills in coding to maintain secure databases, design and implement effective database solutions by adhering to architecture standards, as well as enhance data quality, accessibility, and security. It is essential to optimize new and current database systems and provide operational support for MIS.

Qualifications: The candidate must have a B. Tech/MCA in any technical field with ten years of IT experience with data modelling and global certification in database design for data warehouses.

Urban data analyst at NIUA (National Institute of Urban Affairs)

Location: New Delhi

Responsibilities: The data analyst should write programmes to cleanse and integrate data in a reusable manner while driving optimization and enhancing product development with business strategies. It is needed to assess the accuracy of new data sources and data gathering techniques with the development of custom data models and algorithms through predictive modelling.

Qualifications: The candidate must have a Master’s/Ph.D. in any technical field with two to four years of hands-on experience in the data science field. There should be a strong knowledge of multiple statistical techniques, statistical programming, GIS, data architectures, and Cloud.

Researcher cum data analyst at TISS (Tata Institute of Social Sciences)

Location: Mumbai

Responsibilities: The role is to conduct content and textual analysis of news reports, studies, and articles around the POCSO Act (Protection of Children from Sexual Offences), quantitative data analysis, as well as edit the report prepared.

Qualifications: The candidate must have a Master’s degree in social work or any related field with a minimum of three years of hands-on experience. There should be a strong knowledge of RSS feeds, data scraping, and CMS.

Data scientist supervisor at Los Angeles Public Health Department

Location: Los Angeles County

Qualifications: The candidate must have a Bachelor’s degree in any quantitative field with eight years of hands-on experience including four years of supervising a data science team involving data scientists, data analysts, and many more, or a Master’s degree in any quantitative field with six years of hands-on experience including four years of supervising a data science team.

Senior data scientist at Los Angeles Public Health Department

Location: Los Angeles County

Responsibilities: The senior data scientist needs to provide technical oversight to ensure project success while leading the discovery process to document business requirements and frame business problems. The duty is to correspond data science techniques and support collection and retain requirements for large structured and unstructured data sets from multiple sources, and many more.

Qualifications: The candidate must have a Bachelor’s degree in any quantitative field with six years of hands-on experience including two years of leadership capacity and overseeing applications of machine learning, predictive analytics, data management, and many more in the data science field, or a Master’s degree in any quantitative field with four years of hands-on experience including two years of lead capacity and overseeing applications of machine learning, predictive analytics, data management, and many more in the data science field.

Data scientist at Los Angeles Public Health Department

Location: Los Angeles County

Qualifications: The candidate must have a Bachelor’s degree in any quantitative field with four years of hands-on experience in applying machine learning, predictive analytics, and data management or a Master’s/Ph.D. in any quantitative field with two years of hands-on experience in applying machine learning, predictive analytics, and data management.

Consultant data manager at thsti (Translational Health Science and Technology Institute)

Location: Faridabad, Gurugram

Responsibilities: The roles include providing data management services, exploratory data analysis support, as well as technical support to the consortium. It is also essential to prepare interim reports and review of listings of data for clinical trial status and data extraction while leading in the preparation of datasets for analysis as well as data transfer guidelines for external data load.

Qualifications: The candidate must have a B.E./ B. Tech/ M. Tech/ Ph.D. in Computer Science with four years of experience after Bachelors or two years of experience after Master’s in clinical data management and data analysis. There should be strong knowledge of MySQL, data mining, data cleaning, CDMS, programming language, and many more.

Senior engineer- big data at REBiT

Location: Mumbai

Responsibilities: The senior engineer of big data needs to identify risks and threats based on threat hunts while working with CISO, IT team, and security operations for taking the identified anomalies to a conclusion. The role also includes preparing monthly reports on threat hunts to showcase ROI for all threat hunting programmes with telemetry data.

Location: New Delhi

Responsibilities: n/a

Qualifications: The candidate must have a 12th pass certificate in a science stream with two years of experience in EDP work in any government, autonomous, PSU, or other organization and a speed test of not less than 8000 key depressions per hour through a speed test on computer. The age limit is 28 years.

Project Assistant cum data analyst at ICAR- National Research Centre on Litchi

Location: Muzaffarpur, Bihar

Responsibilities: n/a