Data Science Team Leader
Leads a data science team at GB Corp in Giza, owning the full analytics lifecycle from hypothesis to model delivery. The role blends team leadership with hands-on technical direction in statistical modeling, machine learning, and predictive analytics, plus translating insights for business stakeholders.
- Compensation
- Not disclosed
- Location
- Giza
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Must have
- Lead, mentor, and grow a team of data scientists
- Oversee the full data science lifecycle from hypothesis formation to model delivery
- Guide design and implementation of statistical models and machine learning algorithms
- Experience in data exploration, predictive modeling, and advanced analytics
- Ensure rigor in modeling, validation, and performance measurement
- Best practices in coding, documentation, and reproducible research
- Communicate analytical findings as actionable recommendations to executives and business units
- Collaborate with Data Engineering and AI/ML Engineering teams to operationalize models
Full description
the purpose of Data Science team leader position is to extract actionable insights from data and develop advanced analytics solutions that drive strategic business decisions.
This role focuses on data exploration, predictive modeling, and advanced analytics, ensuring high-quality output that aligns with company objectives.
Team & Project Leadership\:
· Lead, mentor, and grow a team of Data Scientists to deliver high-impact projects.
· Define the team’s roadmap, allocate resources, and set priorities aligned with business goals.
· Oversee the full data science lifecycle, from hypothesis formation to model delivery and insight communication.
Technical Direction\:
· Guide the design and implementation of statistical models, machine learning algorithms, and data experiments.
· Ensure methodological rigor in modeling, validation, and performance measurement.
· Champion best practices in coding, documentation, and reproducible research.
Collaboration & Communication\:
· Work closely with business stakeholders to identify data-driven opportunities.
· Translate complex analytical findings into clear, actionable recommendations for executives and business units.
· Partner with Data Engineering and AI/ML Engineering teams to operationalize models when needed.