- Company Name
- KAINO CONSULTING
- Job Title
- Lead Data Scientist
- Job Description
-
Job Title: Lead Data Scientist
Role Summary: Senior data science leader responsible for designing, developing, and deploying AI models to optimize retail operations, while building and mentoring a high‑performing data science team.
Expectations: Deliver end‑to‑end AI solutions that drive tangible business outcomes; establish data science best practices, standards, and a scalable MLOps pipeline; actively scout and implement emerging AI technologies; communicate model insights to non‑technical stakeholders; maintain high quality and integration of deliverables into business processes.
Key Responsibilities:
- Own the full lifecycle of predictive and prescriptive models (sales forecasting, credit scoring, churn detection, inventory optimization, asset valuation).
- Industrialise models in partnership with Data Engineering, ensuring MLOps practices (monitoring, CI/CD, scalability).
- Define methodological standards, governance, and vision for the Data Science function.
- Recruit, coach, and elevate a team of 2‑3 Data Scientists.
- Supervise deliverable quality and integration into enterprise workflows.
- Collaborate cross‑functionally with Engineering, Analytics, Data Quality, Marketing, Retail, Finance, and HR.
- Initiate and evaluate high‑impact AI use cases.
- Conduct continuous technology scouting in AI, Data Science, and MLOps.
Required Skills:
- Advanced proficiency in Python, SQL, TensorFlow or equivalent ML frameworks.
- Strong experience with cloud platforms, data warehouses (e.g., Snowflake), containerization (Docker), workflow orchestration (Airflow), and MLOps tools (MLflow).
- Proven track record of end‑to‑end data science projects in a commercial setting.
- Leadership and team‑building capabilities; ability to articulate complex AI concepts to non‑technical audiences.
- Excellent written and verbal communication.
Required Education & Certifications:
- Master’s degree (Bac+5) or higher in Applied Mathematics, Statistics, Machine Learning, or a related quantitative discipline.
- Relevant certifications in AI/ML, cloud technologies, or MLOps are advantageous.