Manager leading data science and machine learning initiatives for healthcare payer clients. Focused on operational efficiency, mentoring teams, and actionable insights to reduce costs and improve health outcomes.
About the role
- Lead Data Scientist driving AI strategies and technical solutions in a fast-paced startup. Providing leadership in data science and project management to achieve business goals.
Responsibilities
- Develop and execute AI strategies to achieve business objectives and expand AI capabilities.
- Translate insights from AI projects into actionable recommendations for clients.
- Stay updated on industry trends, competitive landscape, and emerging technologies to inform AI strategies.
- Gather and synthesise customer feedback and market trends to feed back into our product roadmap.
- Manage client accounts, ensuring satisfaction, retention, and alignment of project deliverables with client goals.
- Leads end-to-end project management for data science initiatives, including scoping, planning, stakeholder communication, and delivery of outcomes aligned to business objectives.
- Manage multiple commercial and technical stakeholders effectively. Able to effectively manage executive stakeholders.
- Lead, mentor, and grow a high-performing team of data scientists, ensuring project delivery excellence and professional growth.
- Design end-to-end AI systems that combine models, workflows, automation, and APIs.
- Lead the development and deployment of AI initiatives that address real-world business needs.
- Rapidly develop and iterate on AI prototypes that demonstrate value and feasibility.
- Guide the selection, development, and evaluation of ML and GenAI models for high-impact outcomes.
- Demonstrates proficiency across AI/ML libraries, GenAI platforms, APIs, and deployment frameworks.
Requirements
- 7+ years of hands-on experience in data science or ML engineering, including hands-on experience with Generative AI.
- Proficient in Python, R, SQL; experience with frameworks like TensorFlow, PyTorch, LangChain.
- Proven experience in developing data models and working with modern data stacks (e.g., dbt, Airflow, Snowflake, Databricks, cloud platforms).
- Demonstrated ability to design and implement AI application workflows by orchestrating multiple tools, APIs, and models to deliver end-to-end, production-ready solutions.
- Proven experience in mentoring and leading AI teams to achieve organisational goals.
Benefits
- Health insurance
- Flexible work arrangements
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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