Responsibilities of the Lead Product Manager, Data Science:
- Product Strategy & Roadmap Development-
- Define and execute the product roadmap for data science initiatives aimed at enhancing revenue generation and cost reduction
- Collaborate with business leaders to align product strategy with company goals and market opportunities
- Ensure that all product initiatives are data-driven, measurable, and aligned with business objectives
- Data Science Collaboration-
- Work closely with data science engineers and analysts to identify key insights and opportunities through data
- Translate complex data findings into actionable strategies for the business and product teams
- Oversee the development and optimization of predictive models, algorithms, and machine learning systems
- Revenue & Cost Optimization-
- Focus on driving the development of algorithms and models that optimize pricing, bidding, targeting, and other aspects of programmatic advertising
- Identify key levers to improve profitability through better decision-making processes powered by data insights
- Metrics & Performance-
- Define key performance indicators (KPIs) and success metrics for product initiatives, ensuring constant measurement of impact and effectiveness
- Use data to continuously optimize and refine product offerings, ensuring they meet user needs and business objectives.
Qualifications of the the Lead Product Manager, Data Science:
- Experience & Background-
- 7+ years of experience in product management, with at least 3+ years focused on data science and machine learning. Prior experience in AdTech, Exchange, or Programmatic Advertising environments is a significant advantage
- Proven track record of delivering successful data-driven products that improved business Outcomes
- Strong understanding of data science methodologies, machine learning techniques, and their application to real-world business problems (e.g., predictive modeling, A/B testing, etc.)
- Technical & Analytical Skills-
- Experience working closely with data science engineers and understanding technical challenges and opportunities related to algorithms, models, and data infrastructure
- Proficiency in data analysis tools and languages such as Python, R, SQL, or similar
- Knowledge of key ad-tech concepts including programmatic advertising, demand-side platforms (DSPs), real-time bidding (RTB), and exchange dynamics
- Strategic Thinking-
- Ability to think both strategically and tactically, balancing long-term vision with short-term execution
- Experience in identifying and capitalizing on opportunities to reduce costs and increase revenue through data insights
- Collaboration & Communication-
- Excellent communication skills with the ability to engage and align both technical and non-technical stakeholders
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