Lead Data Scientist

Job Title:

Location:

Salary:

Job Summary:

Lead Data Scientist

Key Responsibilities:

1. Leadership & Strategy

• Lead and mentor a team of Data Scientists and Analysts to design and implement advanced data models and analytics solutions.
• Define and drive the organization’s data science roadmap aligned with product, business, and customer objectives.
• Partner with stakeholders across Product, Engineering, and Business teams to identify high-impact data opportunities.

2. Advanced Analytics & Modelling

• Lead the design, development, and deployment of

  machine learning, AI, and predictive models

  to solve business-critical challenges such as churn prediction, recommendation systems, and behavioral analytics.
• Oversee model validation, optimization, and scalability across production environments.
• Ensure best practices in experimentation, A/B testing, and statistical analysis to support product and marketing decisions.

3. Data Engineering & Integration

• Architect robust data collection and integration pipelines across multiple data sources, including

  Firebase (Firestore, Firebase Analytics)

  and

  BigQuery

  .
• Oversee

  data preprocessing, feature engineering, and ETL pipelines

  to ensure reliability and performance for modelling and analytics.
• Ensure efficient data interoperability across APIs and cloud-based systems.

4. Insights & Visualization

• Deliver actionable insights through compelling visualizations, dashboards, and presentations for executive and operational stakeholders.
• Translate complex analytical findings into clear business recommendations.
• Champion data storytelling to influence strategic decisions across departments.

5. Cloud Model Deployment & Monitoring

• Lead the

  deployment and operationalization

  of ML models on

  Google Cloud Platform (Vertex AI, BigQuery ML)

  or equivalent public clouds.
• Implement robust model tracking, monitoring, and performance management frameworks.
• Proactively manage

  model drift, data quality, and retraining cycles

  for continuous improvement.

6. Collaboration & Communication

• Collaborate closely with cross-functional teams—Engineering, Product, and UX—to integrate intelligent models into applications (including

  React and Firebase-hosted systems

  ).
• Communicate complex data science concepts and project outcomes effectively to technical and non-technical audiences.

Required Skills:

• 7+ years of professional experience in Data Science, with at least 2+ years in a lead or managerial capacity.
• Proven expertise in machine learning, deep learning, and predictive analytics.
• Hands-on experience with Google Cloud Platform (BigQuery, Vertex AI, Cloud Storage, AI Platform) or equivalent cloud infrastructure.
• Strong proficiency in Python and related data science libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, etc.).
• Experience with Firebase, REST APIs, and cloud-based data integration.
• Advanced skills in data visualization and BI tools (Looker Studio, Tableau, or Power BI).
• Solid understanding of data architecture, data modeling, and MLOps pipelines.
• Exceptional leadership, communication, and stakeholder management skills.