Tredence - Data Science Manager

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Role Overview:

We are seeking an experienced Data Science Manager to lead a team of data scientists and analysts in developing data-driven products, insights, and solutions.

The ideal candidate will have a strong background in applied machine learning, data strategy, and stakeholder management, with proven experience in translating business challenges into scalable analytical solutions.

Key Responsibilities:

Leadership & Strategy:

• Lead, mentor, and grow a high-performing data science team.
• Define and execute the data science roadmap aligned with business goals.
• Collaborate cross-functionally with Product, Engineering, and Business units to prioritize projects and deliver measurable impact.

Technical Execution:

• Oversee the design and deployment of predictive models, recommendation systems, and advanced analytics solutions.
• Drive the adoption of best practices in model development, feature engineering, validation, and monitoring.
• Ensure data quality, reproducibility, and governance across all analytics initiatives.

Business Impact:

• Translate complex analytical findings into clear business insights and recommendations.
• Partner with leadership to define KPIs and measure the success of data-driven initiatives.
• Evangelize a data-first culture within the organization.

People Management:

• Hire, coach, and retain top talent in data science and analytics.
• Conduct performance reviews and set clear goals for team members.
• Foster continuous learning, innovation, and collaboration.

Required Qualifications:

• 8 - 14 years of overall experience, with at least 3 - 5 years leading data science or analytics teams.
• Strong understanding of machine learning, statistics, and data modeling.
• Hands-on experience with Python, R, SQL, and modern ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Proven ability to manage projects end-to-end from problem definition to model deployment.
• Experience working with large-scale datasets and cloud platforms (AWS, GCP, or Azure).
• Excellent communication and stakeholder management skills.

Preferred Qualifications:

• Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• Experience in building data products, MLOps, or AI-driven business solutions.
• Exposure to BI tools and data visualization (Tableau, Power BI, Looker).
• Familiarity with experimentation (A/B testing, causal inference) and optimization techniques.

Key Attributes:

• Strategic mindset with hands-on technical expertise.
• Strong business acumen and problem-solving orientation.
• Empathetic leadership and a passion for developing people.
• Curious, data-driven, and committed to innovation.