We 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 Responsibilities :

- Design 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 Skills :

- Forecasting : ARIMA, ETS, Prophet, ML-based forecasting, hierarchical forecasting, causal models

- Proven 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), SQL

- NLP (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 solutions

- Comfort working in a lean, fast-paced, high-ownership consulting environment.

Good to Have :

- Experience with Power BI or other visualization tools

- Exposure to Ops Research / Optimization problems

- MLOps experience : monitoring, model drift detection, automated retraining

- Prior consulting experience or strong client-facing communication skills.

Why Join Us :

- Opportunity to work on diverse forecasting, analytics, and GenAI automation projects

- Small, high-talent team where your work directly impacts client outcomes

- Hands-on exposure to enterprise-grade forecasting systems and LLM-powered tools

- Ownership, learning, and accelerated career growth in a collaborative, non-hierarchical setup