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Senior Data Science Lead - R01571251 at Brillio | Swiftcruit
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 Great 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
