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) |
Required Experience:
Manager
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
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) |
Required Experience:
Manager
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Job Location:
Monthly Salary:
Posted on:
4 days ago
Vacancies:
1 Vacancy
