Position Summary:

We are looking for a Staff Applied Science Manager to lead and grow a team of talented data scientists who have direct impact on our company metrics. The performance of our models and experiments is seen astonishingly quickly – the learning loop is not measured in weeks or days, but hours and minutes. We live in what might be the fastest model-learning playgrounds in the world, with an infrastructure that enables model deployment at both scale and speed.

In this role, you will combine deep technical credibility with strong people leadership. You will build and mentor a high-performing team of data scientists, set technical direction, and drive disciplined program execution across multiple concurrent workstreams. You will sit alongside engineering colleagues who enable our models to deploy, and with a growing variable set of hundreds of potential features, you will lead a highly fertile environment for building, experimenting, refining and achieving real, fast impact.

Who Are You?

• You bring deep expertise and experience in Ad Tech, AI/ML, and Data Science at scale, along with a track record of leading and developing data science talent. Familiarity with big data processing and cloud computing is critical to succeed in this environment.
• In addition to a strong mathematical foundation (Statistics, Probability Theory, Algorithms, Foundations of Machine Learning), you are fluent in data science languages and tools such as Python or Apache Spark, and can guide your team in designing scalable solutions, building proofs-of-concept, and evaluating them offline and online.
• You have a demonstrated ability to manage people – hiring, coaching, and growing data scientists at different stages of their careers – as well as manage programs: planning roadmaps, sequencing priorities, managing dependencies, and ensuring on-time, high-quality delivery across a portfolio of initiatives.
• You are passionate about investigating and learning from data, and about creating an environment where your team is driven to ask interesting and provocative questions and put real models into production that drive real business value.
• You are comfortable balancing hands-on technical involvement with the responsibilities of people management and cross-functional program leadership.
• We are open to diverse academic backgrounds. Our team includes engineers, mathematicians, computer scientists, physicists, economists and social scientists – a rock-star applied science leader can come from any academic field.

What Will You Do?

• Lead and grow a team of data scientists working on one or more data science efforts for InMobi DSP, a gold mine that is being explored for riches. This spans project ideation and conceptualization, solution design, measurement and iteration, coaching, deployment, and post-deployment management.
• Own program execution across your team's portfolio: define roadmaps, sequence priorities, manage dependencies and risks, and ensure initiatives are delivered on time and with high quality.
• Manage, mentor, and develop data scientists – setting clear goals, giving regular feedback, supporting career growth, and building a strong bench of technical talent.
• Remain hands-on where it matters: guide the design, development, and testing of product experiments, and stay close enough to the data and models to unblock your team and make sound technical calls.
• Drive stakeholder management as the interface with internal stakeholders such as Product, Engineering, Data, Infrastructure, and Business teams, translating business needs into technical roadmaps and communicating progress and trade-offs clearly.
• Champion thought leadership for the team. We encourage and support team members to write blogs, commentary, and case studies published on the InMobi blog, and to speak at industry conferences representing InMobi's work.
• Help your team connect model design to business context and end-user needs, and ensure model impact is consistently tied to measurable business outcomes.
• Foster a multi-functional collaboration model, working closely with engineering, product, business, campaign management, and creative development teams, and helping your team draw on the strengths of this diverse group.
• Create the space for your team to experiment with multiple algorithms and learn from what works and what doesn't – reviewing performance, asking why, and adapting techniques to fit the problem at hand, in an environment built for speed.
• Encourage creativity in model design across your team. Model design is not one-size-fits-all; you will guide your team in building layered models and feedback mechanisms for tougher problems in a dynamic environment.
• Represent your team's contributions in the company's broader efforts to innovate and demonstrate thought leadership through products, research papers, and conferences.

Required Skills:

• Master's in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research or Economics, Analytics, or Data Science. Or a Bachelor's from a reputed college with additional relevant experience.
• 10-14 years of work experience in a quantitative field, including model building and validation experience, with at least 2-3 years in a people management or team leadership capacity (direct reports, mentoring, or technical team leadership).
• Proven experience managing programs or portfolios of data science initiatives – setting roadmaps, prioritizing across competing demands, tracking milestones, and driving delivery in a fast-paced environment.
• Ad tech related industry experience is a strong plus. You would have applied algorithms and techniques from Machine Learning, Deep Learning and Statistics or other domains to solve real-world problems and understand the practical issues of using these algorithms on large datasets.
• Comfortable with software programming and statistical platforms such as R, Python etc., including visualization tools.
• Comfortable with the big data ecosystem and Apache Spark. Familiarity with Microsoft Azure, AWS, or Google Cloud/Vertex AI is a bonus.
• Strong track record of hiring, coaching, and retaining data science talent, and of fostering a culture of curiosity, rigor, and accountability within a team.
• Familiarity with the challenges of the identity-less world, particularly for iOS and Android.
• Excellent technical and business communication skills, with the ability to present technical ideas simply to business counterparts and to represent your team's work to senior stakeholders.
• High degree of curiosity, sound judgment in prioritization, and the ability to rapidly learn new areas.