Senior Data Scientist

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 3-5 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 Responsibilitie

• sDesign 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

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Required Skil

• lsForecasting: ARIMA, ETS, Prophet, ML-based forecasting, hierarchical forecasting, causal mode
• lsProven 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 pipeline
• s.Programming: Python (pandas, numpy, scikit-learn, PyTorch/TensorFlow), S
• QLNLP (Foundational): embeddings, transformers, basic extraction/classification (deep expertise not require
• d)LLM Tools: Basic prompt engineering and retrieval-based systems (nice-to-hav
• e)Deployment: Docker, FastAPI/Streamlit, MLflow (preferre
• d)Cloud: Azure or AWS experience (model deployment, storage, CI/C
• D)Strong analytical mindset with the ability to translate real supply chain/business problems into ML solutio
• nsComfort working in a lean, fast-paced, high-ownership consulting environmen

t.

Good to H

• aveExperience with Power BI or other visualization to
• olsExposure to Ops Research / Optimization probl
• emsMLOps experience: monitoring, model drift detection, automated retrain
• ingPrior consulting experience or strong client-facing communication skil

ls.

Why Joi

• n UsOpportunity to work on diverse forecasting, analytics, and GenAI automation proj
• ectsSmall, high-talent team where your work directly impacts client outc
• omesHands-on exposure to enterprise-grade forecasting systems and LLM-powered t
• oolsOwnership, learning, and accelerated career growth in a collaborative, non-hierarchical setup