Kargo creates breakthrough cross-screen ad experiences for the world's leading brands and publishers. Everyday, our 600+ employees bring the power of their creativity and diversity to radically raising the bar on what mobile, CTV, AI, social, and eCommerce can do to wow consumers and build businesses. Now 20 years strong, Kargo has offices in NYC, Chicago, Austin, LA, Dallas, Sydney, Auckland, London and Waterford, Ireland. Humble brag: In 2024, Kargo was recognized as a Best Place to Work by Ad Age and Built In .
Success takes all kinds. Diversity describes our workforce. Inclusion defines our culture. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, marital status, age, national origin, protected veteran status, disability or other legally protected status. Individuals with disabilities are provided reasonable accommodation to participate in the job application process, perform essential job functions, and receive other benefits and privileges of employment.
Director of Data Science
Full-time; In-Office Hybrid Required
NYC
$200,000 - $240,000 OTE
As the Director of Data Science at Kargo, you will play a pivotal role in driving the strategic direction of our adtech company's mission-critical models. You will lead a talented team of 6 to 7 data scientists and machine learning experts, focusing on leveraging the OpenRTB real-time bidding data framework to develop advanced optimizers and audience targeting models. This position requires a blend of technical expertise, leadership skills, and strategic thinking to enhance our modeling infrastructure and address the unique challenges of Kargo's clients.
- Manage and mentor a team of data scientists and machine learning experts, fostering a culture of innovation and excellence.
- Collaborate closely with the bidder team, data engineering, and analytics teams to develop and refine data-driven strategies.
- Work in consultation with product management and business stakeholders to understand client needs and translate them into actionable data science projects.
- Oversee the development and implementation of audience targeting models and optimization algorithms using the OpenRTB framework.
- Ensure the reliability, scalability, and performance of our real-time bidding systems.
- Stay abreast of emerging trends and technologies in adtech, particularly in areas related to machine learning and real-time data processing.
- Drive the continuous improvement of our modeling infrastructure to enhance efficiency and effectiveness.
- Lead the research and development of new methodologies to solve complex problems in audience segmentation and ad targeting.
- Facilitate cross-functional collaboration to ensure alignment of data science initiatives with overall business objectives.
- Present insights and strategic recommendations to senior leadership and stakeholders.
- Advanced degree in Computer Science, Statistics, Mathematics, or a related field.
- Significant experience working with scalable modeling frameworks
- Hands on SQL and Python experience in their past several years
- Extensive experience in data science, machine learning, and adtech.
- Proven track record of leading and managing high-performing data science teams.
- Strong technical expertise in real-time bidding, OpenRTB, and related technologies.
- Excellent communication and interpersonal skills, with the ability to convey complex concepts to non-technical stakeholders.
- Big Picture: kargo.com
- The Latest: Instagram ( @kargomobile ) and LinkedIn ( Kargo )
What We Do
Kargo creates breakthrough cross-screen ad experiences and ad tech solutions for the world’s leading brands, retailers and publishers. Everyday, our 500+ employees bring the power of their creativity and diversity to radically raising the bar on what mobile, CTV, AI, social, and eCommerce can do to wow consumers and build businesses. Now 20 years strong, Kargo has offices in NYC, Chicago, Austin, LA, Sydney, Auckland, London and Waterford, Ireland.
Gallery
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Kargo Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.