ORMAE is a fast-growing consulting firm specializing in Data Science, Optimization, and GenAI solutions across industries. Founded and led by Amit Garg, who holds a Guinness World Record in Mathematics and a PhD in Operations Research, ORMAE excels in delivering cutting-edge solutions at the intersection of technology and business. We are now looking for a hands‑on Data Scientist with about 2-3 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, and DL) for large-scale datasets, including multi‑SKU, multi‑location, and multi‑horizon forecasting.
- Work on complex supply chain datasets covering 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 create adaptive and continuously learning forecasting systems.
- Develop scalable data processing pipelines using Python and Spark (or other distributed frameworks) to efficiently handle millions of records.
- Deploy and monitor forecasting 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.
- Communicate analytical findings clearly with cross‑functional teams, including operations, consulting, and leadership.
Required Skills
- Strong expertise in forecasting techniques: ARIMA, ETS, Prophet, ML‑based forecasting, hierarchical forecasting, and causal models.
- Proven experience handling large‑scale time series datasets (multi‑SKU, multi‑region, millions of rows).
- Hands‑on experience building adaptive forecasting systems, including planner overrides, backtesting, auto‑retraining, and performance KPIs (MAE, MAPE, Bias).
- Proficiency in distributed computing using Spark (PySpark preferred) or equivalent frameworks.
- Strong programming skills in Python (pandas, numpy, scikit‑learn, PyTorch/TensorFlow) and SQL.
- Experience with cloud platforms (Azure or AWS) for model deployment, storage, and CI/CD.
- Strong analytical mindset with the ability to translate complex supply chain and business problems into effective 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 Operations Research or optimization problems.
- MLOps experience, including model monitoring, drift detection, and 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