Data Science Business Analyst

Job Overview :

Were looking for a bridge-builder who can connect the dots between business goals and data science execution. Reporting to the Director/Head of Data Science, youll work across teams to ensure AI/ML/LLM initiatives are well-scoped, documented, and delivered successfully. While youll collaborate closely with Product Management, this role is focused on enabling and delivering Data Science initiatives not on owning the product roadmap.

The right candidate will combine strong business insight, process discipline, and an understanding of the AI/ML development lifecycle to help our Data Science team deliver measurable business impact.

Responsibilities :

1. Requirement Gathering & Alignment :

- Partner with Product Managers, Data Scientists, Engineers, and customer-facing teams to translate business needs into clear, prioritized Data Science requirements.

- Ensure requirements are comprehensive defining what is needed, why it matters, and how it supports broader company goals.

- Maintain traceability from business requirements to Data Science solutions, ensuring scope clarity for all stakeholders.

2. Planning & Documentation :

- Document functional workflows, configuration requirements, and dependencies for DS-powered solutions in partnership with Product Management and UX.

- Consolidate inputs from multiple teams into clear technical plans for the Data Science team.

- Maintain living documentation (Confluence, Jira, Notion, etc.) to ensure transparency and alignment.

3. Stakeholder Coordination & Follow-up :

- Serve as the primary coordinator for cross-functional communication on Data Science initiatives.

- Proactively follow up to unblock dependencies and keep deliverables on track.

- Align DS delivery timelines with Product Owners, Scrum Masters, and Project Managers while respecting established product roadmaps.

4. Process & Outcome Focus :

- Identify and address gaps in processes, documentation, or communication that impact DS delivery.

- Drive initiatives that improve Data Science team efficiency, documentation quality, and cross-team alignment.

- Keep business results, customer impact, and measurable outcomes central to all decision-making.

5. Continuous Improvement :

- Recommend and implement process enhancements for DS project delivery and collaboration.

- Ensure lessons learned from prior initiatives are captured and applied.

- Help foster a culture of transparency, accountability, and continuous improvement within the DS team.

Skills and Tools :

- Understanding of AI/ML Concepts : Not required to code, but must understand ML lifecycle, LLM use cases, and DS product considerations.

- Strong Solution Design Thinking : Ability to translate high-level business goals into actionable DS requirements.

- Excellent Communication & Stakeholder Management : Comfortable working with executives, technical teams, and customer-facing roles.

- Organizational Skills : Able to manage multiple projects, dependencies, and stakeholders with high attention to detail.

- Documentation & Process Management : Experience creating BRDs, PRDs, UI/config plans, and workflow documentation.

- Collaboration Tools : Proficiency in Jira, Confluence, Google Workspace, or similar.

- Problem-Solving : Proactive in identifying bottlenecks, risks, and improvement opportunities.

Preferred Qualifications :

- Prior experience as a Product Analyst, Business Analyst, Product Owner, or similar role in a technology or AI/ML-focused company.

- Exposure to AI/ML/LLM product development and deployment processes.

- Background in analytics, consulting, or technical product management.

Education :

- Bachelors degree in Business, Engineering, Computer Science, or related discipline.

Our Commitment :

At Foundation AI, we're committed to creating an inclusive and diverse workplace. We value equal opportunity and affirmative action principles, giving everyone an equal chance to succeed. We're dedicated to offering equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or veteran status. Upholding these values and adhering to applicable laws is paramount to us.

Competencies :

Must Have Skills :

- Business Requirement Gathering & Analysis : BRDs, PRDs, user stories, acceptance criteria Min 3 Year

- Stakeholder Management : Cross-functional coordination, conflict resolution, influence without authority Min 3 Years

- DS Initiative Planning & Coordination : Jira, Confluence, Trello, Aha, Miro Min 2 Years

- UI/Configuration Planning : Wireframing, workflow mapping, UX collaboration Min 2 Years

- Documentation & Process Management : Confluence, Google Workspace, Notion Min 3 Years

- Understanding of AI/ML & LLM Concepts : ML lifecycle, RAG workflows, prompt engineering fundamentals Min 1 Year

- Dependency & Risk Management : Risk registers, RAID logs, follow-up processes Min 2 Years

- Communication Skills : Clear written/verbal communication for both technical and non-technical audiences Min 3 Years

- Outcome & Customer Focus : Translating technical output into business value Min 3 Years

- Process Improvement & Change Management : Gap analysis, process design, implementation Min 1 Year

- Agile/Scrum Practices : Backlog refinement, sprint planning, retrospectives Min 2 Years

- Collaboration with Technical Teams : DS, ML, Ops, engineering teams Min 2 Years

- Collaboration with Customer-Facing Teams : Delivery, CS, Sales Engineering Min 2 Years