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Tech Stack
Tools & technologiesPySparkPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Design and implement advanced statistical models, including hypothesis testing, regression analysis, and classification algorithms, to drive business outcomes
- Conduct statistical analysis using t-tests, z-tests, and probabilistic graph models to extract insights from large datasets
- Build, train, and deploy predictive models for forecasting and classification using TensorFlow, PyTorch, and Sci-Kit Learn
- Perform data cleaning, transformation, and exploratory analysis using Python, PySpark, R, SAS, or SPSS
- Apply time series forecasting methods, including exponential smoothing, ARIMA, and ARIMAX
- Develop and maintain data validation and monitoring pipelines for data quality and model performance
- Collaborate with cross-functional teams to translate business requirements into analytical solutions and communicate findings
- Automate machine learning workflows to streamline deployment and enhance scalability
Requirements
What you’ll need- At least 5 years of hands-on experience in advanced data science, including statistical analysis and machine learning, and up to 8 years in related roles
- Expertise in hypothesis testing (t-test, z-test)
- Advanced regression analysis (linear and logistic)
- Programming proficiency in Python and PySpark
- Hands-on experience with SAS or SPSS for statistical computing
- Knowledge of probabilistic graph models
- Experience with data validation frameworks such as Great Expectations
- Time series forecasting techniques (exponential smoothing, ARIMA, ARIMAX)
- Familiarity with classification algorithms (decision trees, SVM)
- Experience with machine learning frameworks (TensorFlow, PyTorch, Sci-Kit Learn)
- Proficiency in R for statistical modeling
- Preferred: experience with distance metrics (Hamming, Euclidean, Manhattan)
- Preferred: expertise in model monitoring tools such as Evidently AI
- Preferred: experience deploying models using BentoML
- Preferred: familiarity with ML workflow orchestration tools such as KubeFlow
- Preferred: background designing scalable machine learning pipelines
- Immediate joiner required