Data explosion and the data-driven culture have opened a huge scope for data science in India in recent years. Reputed companies are opening branches in India, especially at Gurgaon which is known as the second-biggest tech hub in the country. It is intimidating to look for good data scientist jobs in the vast field of job opportunities in data science. This article will help data scientists to explore these vacancy alerts for data science jobs in Gurgaon with lucrative salary packages and interesting responsibilities.
Capgemini Invent is the digital innovation, consulting as well as transformation brand of the Capgemini Group. It is known as a global business line combining market-leading expertise in strategy, technology, data science, and creative designs. Capgemini Invent transforms and accelerates ideas into prototypes and scalable real-life solutions for utmost customer satisfaction.
Responsibilities: The candidate is needed to discover hidden information in enormous datasets and help stakeholders take smarter decisions for the future. The candidate is required to understand the business requirements by applying data mining techniques with statistical analysis. The person should provide a suitable approach to solve problems and optimize classifiers, regressors, etc. with machine learning or deep learning techniques. The data scientist should enhance data collection procedures, do ad hoc analysis, and improve analytics delivery procedures.
Qualifications: The candidate needs to be a B.E./B. Tech/M.E./M. Tech/M. Sc. or in other relevant fields such as mathematics, statistics, operational research, computer science, etc. The person should have excellent coding skills in data science languages, statistics skills, and sufficient experience in toolkits like NumPy, Pandas, StatModel, SQL, NoSQL, Text Analysis, Tableau, PowerBI, etc. There should be a clear understanding of machine learning techniques for problems like NN Regression, Naïve Byas, Tree, Random Forests. The candidate is required to have hands-on experience of 3-7 years in the data science field.
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Gartner is known as the world's leading research and advisory company with a combination of expert-led, practitioner-sourced, and data-driven research. It is a trusted advisor and an objective resource for over 14,000 organizations in more than 100 countries. It helps to achieve mission-critical priorities through meaningful in-depth technology insights, advice as well as tools.
Responsibilities: The candidate is required to partner with product managers, business analysts, and data engineers to develop and launch machine learning as well as Artificial Intelligence business capabilities efficiently. The person needs to manage multiple data science projects while owning business goals, KPIs, and other primary initiatives. There should be a responsibility for high-quality data science solutions and mitigating project risks. The candidate should pitch ideas and influence senior leaders while managing, technical mentoring, and developing junior data scientists.
Qualifications: The candidate must have a Bachelor's or Master's degree in any quantitative field with over 8 years of practical experience in building machine learning models, NLP applications, AI business capabilities, Python coding, PySpark, SQL, NoSQL databases as well as deep learning models. There should be a strong working knowledge of Lean product principles, software development lifecycle, etc.
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Genpact is known as a global professional services firm that delivers digital transformation through digital and works to create competitive advantages for clients. It successfully drives digital-led innovation and digitally-enabled intelligent operations for clients. The AI-based platform is known as Genpact Cora accelerates digital transformation in over 30 countries across the world.
Responsibilities: The candidate should be responsible for data extraction, data analysis, data preparation, data modeling as well as data evaluation. The candidate is required to generate statistical forecasts for defined datasets, demonstrate strong analytical and logical skills, present analysis to seniors, and enhance coding as well as debugging skills.
Qualifications: The candidate must have a Master's degree in data science or other relevant fields with hands-on experience as a data scientist with programming languages such as R and Python. There should be a strong knowledge of supply chain management, advanced Excel, VBA programming, basic and intermediate statistics.
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NielsenIQ is popular as the industry leader in global measurement and data analytics with retail and consumer intelligence. It is focused on delivering the complete truth to clients through comprehensive datasets as well as meaningful in-depth insights. It is based in more than 100 countries with a commitment to help clients achieve success in this competitive world.
Responsibilities: The candidate needs to own data science solutions in the field of retail intelligence as per client requests and provide accurate recommendations. The candidate should support internal and external clients with a clear understanding of data science design and methodology. It is necessary to work on new solutions, use cases, proof of concept, and prototypes to automate and develop solutions for existing processes. There should be a strong understanding of Nielsen products and services for overcoming client challenges.
Qualifications: The candidate must have an M.Sc. in statistics, mathematics or other relevant data science certifications with at least 2-4 years of practical experience in data visualization tools, mapping tools, collaboration tools, machine learning, marketing analytics, and so on.
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OLX Group is known as a world-leading and fastest-growing online marketplace company with over 300 million users. It is present in more than 30 countries with over 20 brands available on the trading platform. OLX is focused on developing personalization technologies and optimization strategies to have a direct impact on the users.
Responsibilities: A candidate needs to understand the different buyer segments and buying preferences with content quality assessment and enhancement with Artificial Intelligence. The person is required to look after process and price optimization for increasing the bottom and topliner metrics, drive projects from the data science perspective as well as optimization of models with machine learning solutions. The data scientist needs to measure the impact of models on key metrics while collaborating with the data science community to seek technical solutions and deliver high-quality software against schedules.
Qualifications: The candidate needs to have a clear understanding of machine learning techniques while using libraries like scikitlearn, scipy, etc with a strong engineering background. The candidate also is required to know at least one programming language, especially Python along with practical experience in writing SQL queries, bringing models in production, setting monitoring as well as TensorFlow or MXNET.
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