Lead Product Manager, Data Science
Petach Tikva, Israel
Applications have closed
Digital Turbine
Digital Turbine offers a one-stop platform for user acquisition growth and monetization. Elevate your mobile advertising and experience with us.
At Digital Turbine, we make mobile advertising experiences more meaningful and rewarding for users, app publishers, and advertisers — intelligently connecting people in more ways, across more devices. We provide app publishers and advertisers with powerful ads and experiences that captivate consumers, fuel performance, and help telecoms and OEMs supercharge awareness, acquisition, and monetization. In a rapidly evolving industry, we are constantly innovating and creating better paths of discovery to connect consumers, publishers, and advertisers across the mobile ecosystem.
As the Lead Product Manager, Data Science, you will work closely with cross-functional teams, including data science engineers, software developers, and business stakeholders, to define and drive the product roadmap for our data-driven initiatives. You will focus on leveraging advanced data science and machine learning techniques to uncover insights, optimize models, and develop strategies that increase revenue while reducing costs across our programmatic advertising products.
Digital Turbine (NASDAQ: APPS) powers superior mobile consumer experiences and results for the world’s leading telcos, advertisers and publishers. Our end-to-end platform uniquely simplifies the ability to supercharge awareness, acquisition and monetization — connecting our partners to more consumers, in more ways, across more devices.
The company is headquartered in Austin, Texas, with global offices in New York, Los Angeles, San Francisco, London, Berlin, Singapore, Tel Aviv, and other cities around the world, serving top agency, app developer, and advertising markets.
We are honored to have achieved numerous awards as an employer of choice, around the world, including: BuiltIn's Best Places to Work Awards in 2022, 2023 and 2024, DUNS 100 Best Places to Work in Tech for 2023 and 2024, and BDICode's 100 Best Companies to Work in 2024.
Digital Turbine is an equal opportunity employer committed to exemplifying diversity and inclusion around the world. We welcome people of different backgrounds, experiences, abilities, and perspectives. We embed diversity in our mindset, products, and teams to empower an inclusive, equitable, and culturally fluent environment. Building and continuously fostering this culture within our teams makes us better collaborators, partners, and innovators.
To view our Global Recruitment Privacy Notice, please click here.
Notice to External Staffing Agencies, Placement Services, and Professional Recruiters ("Agencies"):
Digital Turbine will not pay fees for any hires resulting from unsolicited resumes. To protect all parties involved, we only accept resumes submitted directly by candidates. Any unsolicited resumes sent to Digital Turbine, its affiliates, subsidiaries, or employees, through any method (mail, email, etc.), will be considered the property of Digital Turbine and free of any associated fees.
Agencies must obtain prior written approval from Digital Turbine's Talent Acquisition team before submitting any candidate resumes. Resumes may only be submitted in connection with a valid, fully executed contract for services and in response to a specific statement of work. Without such an agreement in place, Digital Turbine will not be responsible for any fees related to submitted candidates.
Agency agreements are only valid if they are in writing and signed by a Digital Turbine officer or an authorized designee. No other Digital Turbine employee has the authority to bind the company to any agreement regarding candidate placement by agencies. Digital Turbine specifically rejects any liability under agreements accepted by negative consent, candidate negotiation, performance, or any means not explicitly outlined above.
As the Lead Product Manager, Data Science, you will work closely with cross-functional teams, including data science engineers, software developers, and business stakeholders, to define and drive the product roadmap for our data-driven initiatives. You will focus on leveraging advanced data science and machine learning techniques to uncover insights, optimize models, and develop strategies that increase revenue while reducing costs across our programmatic advertising products.
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
Digital Turbine (NASDAQ: APPS) powers superior mobile consumer experiences and results for the world’s leading telcos, advertisers and publishers. Our end-to-end platform uniquely simplifies the ability to supercharge awareness, acquisition and monetization — connecting our partners to more consumers, in more ways, across more devices.
The company is headquartered in Austin, Texas, with global offices in New York, Los Angeles, San Francisco, London, Berlin, Singapore, Tel Aviv, and other cities around the world, serving top agency, app developer, and advertising markets.
We are honored to have achieved numerous awards as an employer of choice, around the world, including: BuiltIn's Best Places to Work Awards in 2022, 2023 and 2024, DUNS 100 Best Places to Work in Tech for 2023 and 2024, and BDICode's 100 Best Companies to Work in 2024.
Digital Turbine is an equal opportunity employer committed to exemplifying diversity and inclusion around the world. We welcome people of different backgrounds, experiences, abilities, and perspectives. We embed diversity in our mindset, products, and teams to empower an inclusive, equitable, and culturally fluent environment. Building and continuously fostering this culture within our teams makes us better collaborators, partners, and innovators.
To view our Global Recruitment Privacy Notice, please click here.
Notice to External Staffing Agencies, Placement Services, and Professional Recruiters ("Agencies"):
Digital Turbine will not pay fees for any hires resulting from unsolicited resumes. To protect all parties involved, we only accept resumes submitted directly by candidates. Any unsolicited resumes sent to Digital Turbine, its affiliates, subsidiaries, or employees, through any method (mail, email, etc.), will be considered the property of Digital Turbine and free of any associated fees.
Agencies must obtain prior written approval from Digital Turbine's Talent Acquisition team before submitting any candidate resumes. Resumes may only be submitted in connection with a valid, fully executed contract for services and in response to a specific statement of work. Without such an agreement in place, Digital Turbine will not be responsible for any fees related to submitted candidates.
Agency agreements are only valid if they are in writing and signed by a Digital Turbine officer or an authorized designee. No other Digital Turbine employee has the authority to bind the company to any agreement regarding candidate placement by agencies. Digital Turbine specifically rejects any liability under agreements accepted by negative consent, candidate negotiation, performance, or any means not explicitly outlined above.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
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Categories:
Leadership Jobs
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Tags: A/B testing Data analysis KPIs Machine Learning Predictive modeling Privacy Python R SQL Testing
Perks/benefits: Career development
Region:
Middle East
Country:
Israel
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