About Us
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 SeniorData 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
