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

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