Job Title

About UsWe are a fast-growing consulting firm specializing in Data Science, Optimization, and GenAI solutions across industries. We are now looking for a hands-on Senior Data Scientist with 5+ years of experience who can lead projects end-to-end — from data exploration to scalable deployment — with strong expertise in forecasting, large-scale analytics, and adaptive learning systems.Key ResponsibilitiesDesign and implement advanced forecasting models (statistical, ML, DL) for large-scale datasets, including multi-SKU, multi-location, and multi-horizon forecasting.Work on complex supply chain datasets, including demand planning, inventory movement, lead times, seasonality, promotions, and external drivers.Build and maintain feedback-loop mechanisms with planners (model overrides, adjustments, bias monitoring) to ensure adaptive, continuously learning forecasting systems.Develop scalable data processing pipelines using Python and Spark/distributed frameworks to manage millions of records efficiently.Build NLP components (classification, extraction, embeddings) for analytics use cases where required.Contribute to building and integrating LLM-powered tools (prompting, retrieval, light agent workflows) for automation.Deploy and monitor solutions on Azure or AWS, ensuring reproducibility, version control, and observability of model performance.Collaborate with Power BI experts to integrate model outputs into reports and dashboards for planners and business stakeholders.Contribute to internal accelerators and reusable frameworks for forecasting, MLOps, and cloud-based analytics.Communicate analytical findings clearly with cross-functional teams — including operations, consulting, and leadership.Required SkillsForecasting: ARIMA, ETS, Prophet, ML-based forecasting, hierarchical forecasting, causal modelsProven experience handling large-scale time series datasets (multi-SKU, multi-region, millions of rows).Experience building adaptive/continuous learning forecasting systems, including planner overrides, backtesting, auto-retraining, and KPIs (MAE/MAPE/Bias).Distributed Computing: Spark (PySpark preferred) or equivalent frameworks for scaling pipelines.Programming: Python (pandas, numpy, scikit-learn, PyTorch/TensorFlow), SQLNLP (Foundational): embeddings, transformers, basic extraction/classification (deep expertise not required)LLM Tools: Basic prompt engineering and retrieval-based systems (nice-to-have)Deployment: Docker, FastAPI/Streamlit, MLflow (preferred)Cloud: Azure or AWS experience (model deployment, storage, CI/CD)Strong analytical mindset with the ability to translate real supply chain/business problems into ML solutionsComfort working in a lean, fast-paced, high-ownership consulting environment.Good to HaveExperience with Power BI or other visualization toolsExposure to Ops Research / Optimization problemsMLOps experience: monitoring, model drift detection, automated retrainingPrior consulting experience or strong client-facing communication skills.Why Join UsOpportunity to work on diverse forecasting, analytics, and GenAI automation projectsSmall, high-talent team where your work directly impacts client outcomesHands-on exposure to enterprise-grade forecasting systems and LLM-powered toolsOwnership, learning, and accelerated career growth in a collaborative, non-hierarchical setup