Product Management

Director, Product (mCanvas CTV)

Mumbai
Work Type: Full Time
About Affinity
Affinity is pioneering new frontiers in AdTech by building privacy-first advertising infrastructure that helps publishers maximize monetization and enables advertisers to reach the right audiences beyond walled gardens. Operating across 10+ markets in Asia, the US, and Europe, with a team of 500+ professionals, Affinity continues to innovate at scale in the global AdTech ecosystem.


Role: Director, Product 

Location: Mumbai (Malad)

Product: mCanvas



Roles & Responsibilities: 

  • Translate advertiser, publisher, and platform needs into clear product requirements defining scope, wireframes, and prototypes and partner closely with engineering and AI teams to deliver timely launches.
    Own end-to-end product delivery across a complex AdTech stack, acting as product owner from discovery through launch, enablement, and adoption, covering CTV ad delivery, measurement, optimization, and web/data platforms
  • Partner cross-functionally with Engineering, Data Science, Sales, Customer Success, Marketing, and Business teams to prioritize high-impact initiatives and drive continuous product value across DSP, SSP, and data platforms.
  • Lead strategic collaboration to improve advertiser and publisher outcomes, accelerate adoption, and deliver measurable revenue growth.
  • Apply strong ecosystem judgment by balancing the needs of advertisers, agencies, publishers, OEMs, SSPs, data partners, and internal stakeholders in product decisions.
  • Drive competitive and ecosystem intelligence by tracking customer needs, CTV/AdTech trends, privacy and identity shifts, and partnerships—translating insights into differentiated features, performance gains, and strong product positioning.
  • Lead product discovery and validation through market research, feasibility analysis, and solution evaluation, driving iterative improvements across CTV inventory, targeting, bidding, and measurement.
  • Drive data-led decision-making through experimentation, dashboards, and AI-powered insights across product, campaign, and customer performance. Apply AI/ML capabilities—predictive modelling, optimization, segmentation, fraud detection, and forecasting—by collaborating closely with data science and engineering teams.
  • Strong domain expertise in CTV, programmatic and performance marketing, including DSP/SSP/DMP platforms, audience onboarding, identity resolution, inventory forecasting, bidding strategies, and attribution.
  • Deep technical understanding of AdTech data flows—RTB, ad serving, CTV playback environments, event/log pipelines, attribution (impression/click to conversion), reconciliation, and large-scale data systems for reporting and dashboards.



Required Skills & Experience: 

  • Strong ownership mindset with the ability to operate independently, drive alignment, and manage senior stakeholders in a high-growth startup environment.
  • Bachelor’s degree in Computer Science, Engineering, or a related field; MBA from a top-tier institute preferred.
  • 8+ years of Product Management experience in AdTech/MarTech, delivering complex web, mobile, data-driven, and CTV products.
  • Proven experience leading and mentoring Product Managers and/or Product Analysts.
  • Strong track record building and scaling B2B / Enterprise SaaS products, preferably within AdTech, MarTech, or data platforms.
  • Deep familiarity with programmatic advertising ecosystems, including DSPs, SSPs, DMPs, CTV ad platforms, and measurement/attribution systems.
  • Solid product-level understanding of AI/ML-driven systems, including model training, evaluation, deployment, and iteration (hands-on modelling not required).
  • Working knowledge of AdTech-relevant technologies such as HTML/CSS, browser debugging, APIs, databases, and distributed systems (no coding required).
  • Experience driving usability testing across web, mobile, and CTV applications and translating insights into measurable product improvements.
  • Highly self-motivated, organized, and effective in navigating ambiguity while balancing speed, scale, and technical complexity.

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