Technical Specialist-Data Engg Area(s) of responsibility .

- Data Scientist (Technical Specialist) Specialist Grade Experience: 6–8 years · Location: [To be filled] · Engagement: Full-time Role Expectations Own the design, development, validation, and productionization of AI/ML models for financial forecasting. Analyze historical data to identify predictive features and business-relevant patterns. Develop time-series forecasting models (Prophet, ARIMA, LSTM, XGBoost) tailored to project and quantify forecast accuracy against agreed thresholds. Build a Conversational AI layer using Azure OpenAI RAG patterns to enable naturallanguage queries over financial and workforce data. Partner with FP&A; SMEs to translate business drivers into model features and interpretable outputs.

Reports To Senior Technical

Lead (Python) / Delivery Manager Grade Technical Specialist (above Sr. App Developer, below Sr.

Technical

Lead) Program FP&A; Reporting Automation & AI Forecasting Deliver explainable AI outputs (SHAP, feature importance, etc.) so that Finance users can trust and act on model recommendations. Collaborate with the Sr.

Application

Developer to operationalize models — MLOps pipelines, model registry, monitoring, and retraining triggers. Document experiments, model cards, assumptions, and limitations for audit and governance review.



Must-Have Skills Python for Data Science: 5 years hands-on with pandas, NumPy, scikit-learn, statsmodels, and Jupyter-based experimentation.

Time-Series Forecasting: Deep experience with Prophet, ARIMA/SARIMA, exponential smoothing, XGBoost/LightGBM, and deep learning (LSTM/Transformer) for financial or operational forecasting.

Statistical Modeling: Regression, classification, clustering, feature engineering, hyperparameter tuning, cross-validation, and rigorous model evaluation.

Azure ML Stack: Hands-on with Azure Machine Learning (AML), MLflow, Azure OpenAI, and model deployment as endpoints or batch jobs. LLM & GenAI: Practical experience with prompt engineering, RAG (Retrieval-Augmented Generation), embeddings, vector stores (Azure AI Search / FAISS / Pinecone), and LangChain or Semantic Kernel.

Explainability: SHAP, LIME, partial dependence plots, and communicating model behavior to non-technical Finance stakeholders. Preferred / Positive-to-Have Skills Prior experience with Finance / FP&A; / Corporate Planning use cases.

- Exposure to Energy, Oil & Gas, or EPC project economics • Exposure to agent frameworks (LangGraph, AutoGen, Semantic Kernel) for building autonomous analytical agents.

Experience Level Mid Level

📌 Technical Specialist - Data Engineering and AI/ML Forecasting (Pune)
🏢 Birlasoft
📍 Pune