Data Science Manager
- Compensation
- Not disclosed
- Location
- Pune, Maharashtra, India
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Full time
- Experience
- 8+ years
- Category
- Data science
- Posted
Skills
Must have
- Pharmaceutical Domain: Relevant exposure to the pharmaceutical industry or pharma-related data science projects.
- Probability and Statistics: Advanced knowledge of statistical methods, probability theory, and analytical techniques.
- Machine Learning: Advanced understanding of practical machine learning methods, model evaluation, common pitfalls, and mitigation approaches.
- SQL and Python: Intermediate proficiency in SQL and Python for data analysis, querying, and analytical problem-solving.
- Project Management: Intermediate knowledge of project management methodologies, planning tools, milestone tracking, and delivery processes.
- Client and Stakeholder Management: Ability to gather requirements, communicate progress, manage expectations, and maintain strong client relationships.
- Leadership: Experience guiding team members, reviewing deliverables, and maintaining high standards of execution.
- MS Office: Intermediate proficiency in Microsoft Excel, PowerPoint, and Word for analysis, reporting, and presentations.
- Quality and Delivery Management: Ability to monitor project performance, identify delivery risks, and implement quality improvement initiatives.
Full description
This role is for one of Weekday’s clients
Min Experience: 8+ years
Location: Pune, Maharashtra, India
JobType: full-time
We are looking for an experienced and results-oriented Data Science Manager to lead the delivery of data science and machine learning projects, with a focus on pharmaceutical and healthcare-related business challenges. The role involves collaborating with engagement managers, account delivery teams, and client stakeholders to understand business requirements, design analytical solutions, and ensure high-quality project execution.
The ideal candidate will combine strong expertise in probability, statistics, and practical machine learning with working knowledge of SQL, Python, and project management methodologies. They should be capable of translating business problems into effective data science solutions, guiding technical teams, managing client expectations, and ensuring projects are delivered within the agreed scope, timelines, and quality standards.
Requirements
Key Responsibilities
1. Client Engagement and Requirement Gathering
- Collaborate with engagement managers, account delivery managers, and client stakeholders to understand business objectives, project requirements, and expected outcomes.
- Translate business requirements into well-defined analytical problems and data science project deliverables.
- Maintain effective communication with clients throughout the project lifecycle and ensure alignment on scope, milestones, and priorities.
- Lead client meetings, weekly business reviews, and project discussions to communicate progress, address challenges, and agree on next steps.
2. Data Science Solution Design
- Develop appropriate data science and machine learning approaches to address client business challenges.
- Apply advanced knowledge of probability and statistics to analyse data, validate assumptions, and generate meaningful insights.
- Design practical machine learning solutions while accounting for common pitfalls, model limitations, data quality issues, and potential sources of bias.
- Guide the selection of suitable analytical methodologies, modelling techniques, and evaluation metrics based on project objectives.
- Use SQL and Python to support data exploration, analysis, model development, and validation as required.
3. Project Planning and Delivery Management
- Develop comprehensive project plans covering scope, objectives, resource allocation, milestones, timelines, and deliverables.
- Allocate tasks to team members based on their skills, experience, and project requirements.
- Lead project execution and monitor progress against agreed plans, identifying risks and implementing corrective actions where necessary.