Senior Data Science Lead

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Job requirements

Experience Range: With at least 8 years of experience in data science and advanced analytics, including recent leadership roles spanning up to 12 years Key Responsibilities:
- Lead the design, development, and implementation of advanced statistical models and machine learning solutions to address complex business challenges and deliver measurable impact
- Drive end-to-end data science project lifecycles, overseeing data exploration, hypothesis testing, feature engineering, model selection, and validation
- Apply regression, classification, and forecasting techniques such as ARIMA, ARIMAX, exponential smoothing, and decision trees to generate predictive analytics and actionable insights
- Collaborate with cross-functional teams to translate business objectives into actionable data science strategies and ensure alignment with organizational goals
- Build, evaluate, and deploy scalable machine learning models using Python, PySpark, R, TensorFlow, PyTorch, and Sci-Kit Learn
- Monitor data quality, bias detection, and model performance using Excellent Expectations and Evidently AI, ensuring robust analytics outcomes
- Mentor and guide junior data scientists, providing technical leadership, conducting code reviews, and promoting best practices in statistical analysis and machine learning
- Present findings and insights to stakeholders through clear visualizations and presentations, facilitating data-driven decision making
Required Skills:
- Advanced proficiency in Python and PySpark for data processing and modeling
- Expertise in statistical analysis, including hypothesis testing,



t-tests, and z-tests
- Strong knowledge of regression techniques (linear, logistic) and classification algorithms (decision trees, SVM)
- Hands-on experience with probabilistic graphical models for complex data relationships
- Proficiency with machine learning frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet
- Experience with forecasting methods including exponential smoothing, ARIMA, and ARIMAX
- Competence in data quality and monitoring tools such as Great Expectations and Evidently AI
- Working knowledge of SAS or SPSS for statistical analysis and computing
- Familiarity with R and R Studio for advanced analytics
- Understanding of distance metrics such as Hamming, Euclidean, and Manhattan
Preferred Skills:
- Experience deploying machine learning models in production environments using KubeFlow or BentoML
- Expertise in developing scalable data pipelines for machine learning workflows
- Knowledge of advanced feature engineering and dimensionality reduction techniques such as PCA and t-SNE
- Background in model interpretability and explainable AI methodologies (e.g., SHAP, LIME)
- Exposure to real-time analytics and streaming data platforms such as Apache Kafka or Spark Streaming
Desired Qualifications:
- Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline
- Microsoft Certified: Azure Data Scientist Associate or TensorFlow Developer Certificate (preferred)
- Formal training or certification in advanced statistical analysis or machine learning frameworks

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📌 Senior Data Science Lead251 (Bengaluru)
🏢 Brillio
📍 Bengaluru