Senior Data Scientist Remote

Senior Data Scientist

Key Responsibilities

Advanced ML Algorithms

• Design, train, and evaluate supervised & unsupervised models (regression, classification, clustering, uplift)
• Apply automated hyperparameter optimization (Optuna, HyperOpt) and interpretability techniques (SHAP, LIME).

Data Analysis & Feature Engineering

• Perform deep exploratory data analysis (EDA) to uncover patterns & anomalies
• Engineer predictive features from structured, semistructured, and unstructured data; manage feature stores (Feast).
• Ensure data quality through rigorous validation and automated checks.

TimeSeries Forecasting (Demand)

Build hierarchical, intermittent, and multiseasonal forecasts for thousands of SKUs.

Implement traditional (ARIMA, ETS, Prophet) and deeplearning (RNN/LSTM, TemporalFusion Transformer) approaches.

Reconcile forecasts across product/category hierarchies; quantify accuracy (MAPE, WAPE) and bias.

MLOps & Model Lifecycl

Establish model tracking & registry (MLflow, SageMaker Model Registry).

Develop CI/CD pipelines for automated retraining, validation, and deployment (Airflow, Kubeflow, GitHub Actions).

Monitor data & concept drift; trigger retuning or rollback as needed.

Statistical Analysis & Experimentation

Design and analyze A/B tests, causal inference studies, and Bayesian experiments. Provide statisticallygrounded insights and recommendations to stakeholders.

Minimum Qualifications

• M.S. in Statistics

  (preferred) or related field such as Applied Mathematics, Computer Science, Data Science.

• 4+ years

  building and deploying ML models in production.
• Expertlevel proficiency in Python (Pandas, NumPy, SciPy, scikitlearn), SQL, and Git.
• Demonstrated success delivering largescale demandforecasting or timeseries solutions.
• Handson experience with MLOps tools (MLflow, Kubeflow, SageMaker, Airflow) for model tracking and automated retraining.