Were searching for an experienced Senior Data Scientist who excels at statistical analysis, feature engineering, and endtoend machinelearning operations. Your primary mission will be to build and productionize demandforecasting models across thousands of SKUs, while owning the full model lifecyclefrom data discovery through automated retraining and performance monitoring. 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.
Role & responsibilities Independently lead and deliver a few analytics projects at a time. Acts as the analytics translator and negotiator between the business and data science teams. Understand project scope/requirements, define and own the successful delivery of analytics projects on time and on budget. Drive technical and business teams to meet project milestones through collaboration and influence. Own all communication channels pertaining to assigned projects, including regular stakeholder review meetings. Work closely with the business and segment analytics leads to help drive adoption of proven and deployed analytics solutions. Track business impact/value enabled through analytics solutions. Train and mentor junior project managers. Lead end-to-end project delivery for data, BI, and AI-focused initiatives. Develop and manage detailed project plans, resource allocations, budget recovery and timelines. Ensure clear, concise, and confident communication across teams, including senior leadership. Prepare and deliver executive-level presentations and project updates. Proactively manage risks, issues, and dependencies to ensure successful delivery. Build strong relationships with business, IT, and external stakeholders. Drive continuous improvement in project management processes and team collaboration. Ensure alignment with business goals, timelines, and quality standards. Preferred candidate profile 8+ years of experience in project/program management. Proven experience in leading BI and AI programs independently successfully. Excellent communication skills (verbal, written, and visual) must be able to present with clarity and confidence. Must have experience presenting projects to senior business and technical executives. Expertise in PowerPoint and building professional-quality decks. Strong budgeting skills with ability to proactively identify risks to budget and timelines. Deep experience in stakeholder management and cross-functional collaboration. Strong problem-solving and detail-oriented execution capability. Strong experience with Agile/Scrum methodologies and tools like Jira, Asana, or MS Project. Experience in leading cross-functional and globally dispersed project team. Preferred Qualifications Certifications: PMP, PRINCE2, or Agile-Scrum. Technical knowledge in AWS, Databricks, Power BI, Tableau, and AI/ML technologies. Experience with data science, data visualization tools, including R, Tableau, Power BI, and Python.