Data Scientist

Job Description

Kalina , Mumbai, Maharashtra, India Department DIGITAL Job posted on Jun 02, 2025 Employee Type Permanent Experience range (Years) 4 years - 9 years Key Responsibilities: Lead the design, development, and deployment of predictive models, optimization algorithms, and statistical analyses. Translate complex business problems into data science solutions using machine learning, deep learning, NLP, and statistical modeling. Collaborate with product managers, engineers, and business stakeholders to understand objectives and deliver actionable insights. Mentor junior data scientists and analysts, and drive best practices in experimentation, coding standards, and model governance. Conduct exploratory data analysis, feature engineering, and model validation to ensure accuracy and robustness. Present findings and recommendations clearly to both technical and non-technical stakeholders. Stay up to date with the latest trends in AI/ML, and recommend new tools or techniques as appropriate. Contribute to the development of data science pipelines and MLOps practices for scalable and reproducible model deployment. Qualifications: Master’s or PhD in Computer Science, Statistics, Mathematics, Data Science, or related field. 8+ years of experience in data science, analytics, or machine learning roles. Strong proficiency in Python (pandas, scikit-learn, NumPy, TensorFlow/PyTorch) and SQL. Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Solid understanding of data structures, algorithms, and statistical concepts. Hands-on experience in NLP, time series forecasting, recommender systems, or computer vision is a plus. Strong communication and storytelling skills, with the ability to influence decision-making. Experience with version control (Git), CI/CD pipelines, and ML lifecycle management tools (MLflow, Airflow, etc.) is desirable. Preferred Qualifications: Prior experience in industries like finance, healthcare, retail, telecom, or manufacturing. Experience working with large-scale data processing frameworks (e.g., Spark, Hadoop). Knowledge of generative AI or LLM-based applications is a bonus.