Senior data scientist

12 hours ago

Chennai, India Mastech Digital Full time

Role - Senior Data Scientist Location – Chennai, TN (Hybrid) Role Overview: As a Senior Data Scientist, you will play a pivotal role in shaping our data-driven strategy and providing advanced analytical insights that drive key business decisions. You will work closely with cross-functional teams to identify opportunities, develop predictive models, and transform data into actionable insights. With your extensive experience in data science and machine learning, you will be responsible for leading complex projects, mentoring junior team members, and contributing to the advancement of our data science capabilities. Key Responsibilities: 1. Leadership: Provide thought leadership in the field of data science, guiding the organization in developing a comprehensive data strategy and roadmap. 2. Advanced Analytics: Design and implement advanced analytical models to solve complex business problems, including predictive and prescriptive Modelling, clustering, and optimization. 3. Data Exploration: Explore and analyse large and complex datasets to uncover hidden patterns, trends, and insights that can drive strategic decisions. 4. Model Development: Lead the end-to-end development of machine learning models, from data collection and preprocessing to model training, evaluation, and deployment. 5. Cross-Functional Collaboration: Collaborate with teams across the organization, including pre-sales, product development, and operations, to identify opportunities for data-driven decision-making. 6. Mentorship: Provide guidance and mentorship to junior data scientists, helping them improve their skills and contribute effectively to projects. 7. Innovation: Stay up to date with the latest advancements in data science and machine learning, and actively seek opportunities to apply new techniques to business challenges. Requirements & Skills: 1. Education: A Master's or Ph. D. in a relevant field such as Computer Science, Statistics, Mathematics, or a related discipline. 2. Experience: A minimum of 8 years of professional experience in data science, with proven experience as a Data Scientist with a focus on machine learning and statistical modelling and ability to lead and deliver complex projects. 3. Communication Skills: Strong verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders. 4. Teamwork: Demonstrated ability to work effectively in cross-functional teams and mentor junior team members. 5. Problem Solving: Strong problem-solving skills and a creative approach to finding innovative solutions to complex challenges. 6. Adaptability: Flexibility to adapt to changing project requirements and business needs. 7. Machine Learning Expertise: Strong hands-on experience in machine learning algorithms and techniques, including regression, classification, clustering, and deep learning. Experience in deploying machine learning models into production systems, including containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes). 8. Programming Skills: Proficiency in programming languages such as Python and Py Spark. Familiarity with relevant libraries e.g., Tensor Flow, Py Torch, scikit-learn, etc. Experience with other programming languages like Java or C++, R, Scala etc. 9. Data Handling: Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques. Good understanding of big data technologies and tools (e.g., Hadoop, Spark) as well as distributed computing concepts for working with large-scale datasets. Proficiency in SQL for data extraction and manipulation. Knowledge of Graph DB is added advantage. 10. Data Visualization: Experience with data visualization tools such as Tableau, Power BI, Matplotlib, etc. for creating insightful visualizations. 11. Cloud Computing: Experience with cloud computing platforms such as AWS, Azure, or Google Cloud for data storage, processing, and model deployment. 12. Statistical Analysis: Profound knowledge of statistical analysis and hypothesis testing. 13. Dev Ops: Experience in Dev Ops practices and continuous integration/continuous deployment (CI/CD) pipelines for automating model deployment and updates. Proficiency with version control systems like Git for managing code, scripts, and model versions. 14. Domain Knowledge: Good understanding of the industry and business domain in which the company operates, enabling you to align data science efforts with business objectives. Join us as a Senior Data Scientist, leveraging your profound expertise and rich experience to drive our data-driven initiatives to new heights. With your leadership and strategic insights, you'll lead our data science team to uncover valuable insights and shape the future of our organization. Apply today to be a catalyst for innovation and excellence in data science.

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