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Lead Product Manager, Data Science

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.


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


About Digital Turbine:


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.


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Average salary estimate

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What You Should Know About Lead Product Manager, Data Science, Digital Turbine

Join Digital Turbine as our Lead Product Manager for Data Science, where you'll dive into the exciting world of mobile advertising! We’re looking for an innovative thinker who can connect the dots between data science and product management to create impactful solutions. In this role, you'll work closely with talented data scientists, engineers, and business stakeholders to shape the product roadmap that drives our data-driven initiatives forward. You’ll harness the power of advanced data science techniques and machine learning to uncover insights and enhance our programmatic advertising products. Your skills in product strategy and roadmap development will help us identify new opportunities that not only optimize revenue generation but also reduce costs. We’re all about collaboration at Digital Turbine, so you'll be instrumental in translating complex data findings into actionable strategies. If you have experience in the AdTech realm, a deep understanding of market dynamics, and a passion for strategy, you’re going to thrive here. As we continue to innovate in a fast-paced environment, your ability to define key performance indicators and optimize our offerings will be crucial for long-term success. Join us in our mission to create meaningful advertising experiences that connect consumers, advertisers, and publishers more effectively than ever!

Frequently Asked Questions (FAQs) for Lead Product Manager, Data Science Role at Digital Turbine
What does the Lead Product Manager position at Digital Turbine involve?

The Lead Product Manager role at Digital Turbine involves defining and executing the product roadmap for data science initiatives, collaborating with cross-functional teams, and leveraging advanced data science techniques to improve revenue and reduce costs across programmatic advertising products.

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What qualifications are required for the Lead Product Manager, Data Science role at Digital Turbine?

To be eligible for the Lead Product Manager, Data Science position at Digital Turbine, candidates should have over 7 years of experience in product management with at least 3 years focused on data science. A background in AdTech and knowledge of relevant methodologies such as predictive modeling and A/B testing are highly advantageous.

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What are the key responsibilities of the Lead Product Manager, Data Science at Digital Turbine?

Key responsibilities include developing the product strategy and roadmap, collaborating with data scientists to translate data insights into actionable strategies, optimizing pricing and bidding algorithms, and defining key performance indicators to measure the success of product initiatives.

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How does Digital Turbine support diversity and inclusion in the workplace?

Digital Turbine is committed to fostering a diverse and inclusive workplace by welcoming individuals from various backgrounds, experiences, and perspectives. This commitment enhances collaboration and innovation across teams, making us a better organization.

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What kind of innovative tools and technologies does the Lead Product Manager, Data Science at Digital Turbine get to work with?

The Lead Product Manager for Data Science will work with advanced data science tools and technologies, such as machine learning algorithms, predictive models, and data analysis tools like Python, R, and SQL to drive data-driven decision-making and product optimization.

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What is the company culture like at Digital Turbine?

At Digital Turbine, the culture is centered around innovation, collaboration, and continuous learning. We prioritize a work environment that encourages ideas and creativity while maintaining a strong commitment to diversity and inclusion.

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How can I prepare myself for an interview for the Lead Product Manager, Data Science role at Digital Turbine?

Preparing for an interview at Digital Turbine for the Lead Product Manager, Data Science role involves brushing up on your knowledge of data science methodologies, understanding the company’s product offerings, and being ready to discuss your strategic thinking and past successes in product management.

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Common Interview Questions for Lead Product Manager, Data Science
Can you describe your experience with data-driven product management?

In your response, focus on specific products you've managed that utilized data analysis for decision-making. Highlight how data insights led to measurable business outcomes, such as improved user engagement or revenue growth.

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How do you define success for a product initiative?

Discuss the importance of establishing clear KPIs and success metrics at the outset of each project. Provide examples of how you have measured success in the past and how those metrics informed future product improvements.

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Give an example of a time you worked with cross-functional teams. What challenges did you face?

Share a specific instance demonstrating your collaborative approach. Highlight how effective communication helped overcome challenges and led to successful outcomes. Emphasize your role in aligning team objectives.

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How do you approach the product roadmap development process?

Explain your strategy for developing a product roadmap, emphasizing the importance of aligning it with business goals. Use past experiences to illustrate how customer feedback and market research informed your roadmap decisions.

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What methodologies are you familiar with regarding data science and machine learning?

List the methodologies you have experience with, such as A/B testing, predictive modeling, or clustering. Provide examples of how you applied these methodologies in real-world scenarios to drive product decisions.

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How do you handle competing priorities when managing multiple product initiatives?

Discuss your approach to prioritization, including how you assess the impact of each project. Give an example of a time when you had to balance multiple initiatives and the strategies you used to successfully manage them.

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Describe a product you launched successfully. What was your role?

Share details of a specific product launch, your responsibilities, and the steps you took to ensure its success. Focus on your contributions to strategy development, team collaboration, and post-launch analysis.

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How do you stay updated on the latest trends in data science and product management?

Mention any resources you use, such as industry publications, conferences, or webinars. Highlight the importance of continuous learning and how you apply insights gained to your product management practices.

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What role does user feedback play in your product management strategy?

Stress the importance of gathering and incorporating user feedback throughout the product lifecycle. Provide examples of how user insights have led to product refinements or new feature development.

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How do you balance technical requirements with business needs in product development?

Discuss your approach to finding a balance between technical feasibility and aligning product features with business objectives. Use an example to demonstrate how you've successfully navigated this balance in a previous role.

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The leading independent mobile growth platform — leveling up the landscape for advertisers, publishers, carriers and OEMs.

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DATE POSTED
November 25, 2024

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