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
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)
Required Experience:
Director
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 ana...
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
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)
Discover a world of financial solutions at Aditya Birla Capital – your trusted partner for investments, insurance, loans, and a wide range of financial services in India.
Job Location:
Monthly Salary:
Posted on:
Vacancies:
