Senior Data Scientist – Python / SQL – New York, NY / Hybrid – Marketing / Media – $130,000 – $150,000 + Benefits

Our client is a modern marketing company engineered for the unprecedented opportunities and challenges facing marketers today. They are known for pairing the brightest data scientists with award-winning creatives, strategists, engineers and expert research teams to produce some of the most innovative and cutting-edge creative work in culture.

Their clients span the leading brands in finance, technology, media, CPG, real estate, and many other categories. These partnerships have earned them multiple awards and recognition.

About the role

The Skeptic team builds the tools that power the media buying practice and elevate client campaigns. Their work ranges from predictive modeling and optimization to infrastructure development, pushing the limits of advanced advertising.

They are seeking a Senior Data Scientist who can understand the core business objectives of internal stakeholders and clients, and develop tools tailored to specific use cases. Media experience is a plus but not required. The initial focus of this role will include a strong forecasting component, leveraging techniques commonly used in Media Mix Modeling.

In this position, you will guide other data scientists across a variety of projects, collaborate cross-functionally, and drive some of the most complex and high-impact data science initiatives within the organization.

Who you are and what you have

• A Master's or PhD from a well-regarded college or university (STEM degrees preferred).
• 5+ years (with Masters) or 3+ years (with PhD) of hands-on experience in quantitative analysis, statistical modeling, optimization and/or statistics. Candidates with a Bachelor's degree and 7+ years of experience may also be considered.
• 3+ years of experience building data science software.
• Strong experience utilizing Python and SQL.
• Experience in ad-tech or media buying is highly desirable, particularly modeling data from “Walled Garden” social ecosystems.
• Strong understanding of Bayesian statistical methods and probabilistic thinking beyond traditional frequentist approaches.
• Proven ability to translate business challenges into quantitative solutions, using machine learning or alternative analytical approaches as needed.
• Demonstrated ownership of projects from concept through completion.
• Commitment to maintaining high standards of quality and accuracy in analytics.
• Experience working within a tech team environment, including cloud technologies and version control.
• Experience in advertising or advertising technology is a plus.
• Applied knowledge of Bayesian inference and probabilistic programming (e.g., PyMC) is a plus.
• Deep understanding of social advertising platform data structures and optimization levers (bidding strategies, conversion windows, attribution logic) is a plus.

What you’ll do: 

• Develop new techniques (e.g., machine learning models, optimization algorithms, automation frameworks) to improve internal IP and create tools for clients.
• Work with data scientists and engineers to productionalize new tools and ensure scalability and reliability.
• Collaborate with data visualization experts to build dashboards around forecasts and model outputs.
• Manage the ingestion, cleaning, and preparation of new datasets relevant to ongoing projects.
• Mentor and guide other data scientists on the team.
• Drive forward complex, high-impact data science projects from ideation through delivery.

Some of the perks

• Unlimited paid time off
• 401k with company matching and no vesting period
• Annual bonuses
• Generous medical plan
• Paid parental leave

How do you apply?

If you are interested in applying for the Senior Data Scientist role, please do so via the link on this page or contact Digital Republic on the phone or email. 

Contact us to find out more:

Get in contact with Digital Republic Talent by sending a mail to [email protected]. Check out the website at www.digitalrepublictalent.com. You can also find out more on LinkedIn, Instagram or Facebook