- Company Name
- Artefact
- Job Title
- Data Scientist Manager
- Job Description
-
**Job Title:** Data Scientist Manager
**Role Summary:**
Lead a cross‑functional data science team to design, deliver, and scale AI solutions for clients. Own end‑to‑end project delivery, ensure technical excellence through MLOps and software engineering best practices, and act as the primary technical liaison with senior business stakeholders.
**Expectations:**
- Minimum 5 years of hands‑on experience building data‑driven products.
- Proven expertise in applied machine learning, generative AI, and industrializing AI workflows on cloud platforms.
- Strong leadership, stakeholder management, mentoring, and business communication skills.
**Key Responsibilities:**
- Define and execute client projects from use‑case scoping to production deployment.
- Champion software engineering and MLOps standards to deliver scalable, maintainable solutions.
- Evaluate data availability and architecture options; challenge business requirements to select optimal methods.
- Serve as the technical reference for clients, translating AI concepts into business value and ROI insights.
- Build and maintain long‑term client relationships with C‑level and operational teams.
- Lead, staff, and coach the national data science team; manage hiring, performance reviews, and career development plans.
- Promote continuous learning through workshops, documentation, and internal knowledge sharing.
- Identify and prototype reusable modules, tools, and accelerators across projects.
- Monitor emerging tools, frameworks, and cloud services; advise on technology adoption.
- Manage project risks, unblock teams, and ensure timely delivery while balancing ambition and feasibility.
- Foster collaboration between data scientists, data engineers, and business units to ensure solution adoption.
**Required Skills:**
- Leadership & team management
- Stakeholder communication (C‑level to operational)
- Advanced machine learning (supervised, unsupervised, generative models)
- MLOps, CI/CD for ML, reproducible pipelines
- Cloud AI services (AWS SageMaker, GCP Vertex AI, Azure ML, etc.)
- Software engineering fundamentals (code quality, version control, testing)
- Problem‑solving, analytical thinking, and creativity
- Mentoring, coaching, and performance feedback
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Data Science, Applied Mathematics, Statistics, or related field (equivalent industry experience acceptable).
- Professional certifications in cloud platforms (e.g., AWS Certified Machine Learning – Specialty, GCP Professional Data Engineer, Azure Data Scientist Associate) are a plus.