TM Data Science

Aditya Birla Group

Mumbai, India

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Job Description

Job Purpose :

The role is responsible for delivering specific advanced analytics projects and drive data-driven decision-making and innovation within the organization. This role involves identifying projects, understanding the business need, delivering the development and implementation of advanced analytics, machine learning models, and data strategies to solve complex business problems individually or with team of data scientists. The Senior TM Data Scientist will collaborate with cross-functional teams to ensure the effective use of data, provide strategic insights, and contribute to the overall growth and success of the company.

The Senior Data Scientist will operate with a 50% focus on individual contribution and a 50% focus on team management.

4) Key Result Areas/Accountabilities:

Non-Technical Skills
Category	Step/Activity	Supporting Actions
Analytics Delivery	Use Case / Project Identification	.Supportsthe VH Digital and Analytics COE in brain storming for use cases.
. Design & Implement prioritization, benchmarking, and feasibility assessment framework aligned with VH Digital and Analytics COE
.Leadtranslation of business problems into analytics problem statements
Project Execution	.Design & Implement project charter creation (potential timelines, proposed solution architecture, business KPIs, etc.) aligned with VH Digital and Analytics COE
. Lead & Implement - end-to-end project delivery - technical standards - data preparation, feature engineering, and model development - reproducible pipelines, experiment tracking, and versioning - evaluation framework, success metrics, and business validation .Review - Team member project implementation to ensure code and model quality
Model Monitoring	. Design & Implement - model performance - data quality - drift monitoring . Lead root-cause analysis and retraining decisions
Solution Adoption	. Design & Lead deployment approach and integration into business processes . Support user onboarding and adoption tracking
People Management	Team Management	. Design & Implement skill roadmaps and development plans (DS and CDS) . Mentor junior team members (DS, CDS) through reviews and guidance
Training & Knowledge Sharing	. Design & Implement training on DS best practices, tools, and frameworks . Lead knowledge sharing within DS community
Business Alignment	Stakeholder Management	. Lead & Implement stakeholder communication and progress reviews . Execute translation of analytics outcomes to business impact

Non-Technical Skills
Category	Supporting Actions
Core Skills	Concepts (Technical) a) Problem framing, EDA, feature engineering b) Statistical reasoning and ML fundamentals Concepts (Soft Skills) a) Technical leadership and mentoring b) Business storytelling and stakeholder communication Tools Python, SQL, R pandas, numpy scikit-learn Jupyter, VS Code Git
Advanced Skills	Concepts a) End-to-end ownership of ML, DL, CV, NLP, GenAI solutions b) Model robustness, monitoring, and optimization Tools ML: XGBoost, LightGBM DL: TensorFlow, PyTorch CV: OpenCV NLP/GenAI: spaCy, HuggingFace, LangChain, LLM APIsMLOps: MLflow, Airflow, Docker
Optional Skills	Concepts a) Advanced experimentation and solution innovation b) Optimization-driven decision making Tools OR-Tools, PuLP, Prophet, Evidently, Kubernetes, Azure/AWS (any one)