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Rockerbox

Data Science Manager

Posted 14 Days Ago
Remote
Senior level
Remote
Senior level
Lead and mentor the data science team, develop statistical models, drive data science initiatives, and collaborate with cross-functional teams.
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Data Science Manager

Rockerbox empowers marketing executives to confidently make data-driven decisions, helping brands such as Tula, Figs, and Burton with the strategic decision-making that drives growth. To do so, Rockerbox offers a unique suite of product lines that centralize data and offer diversified measurement methodologies. The foundation of Rockerbox's solution is data centralization. Atop this foundation, the platform enables marketers to choose from a range of measurement methodologies, giving customers the flexibility to choose the most appropriate approach for their specific needs and questions.

As the Data Science Manager at Rockerbox, you will lead and scale our data science team while also contributing as a hands-on practitioner. This role is a player-coach position, balancing leadership responsibilities with direct execution in feature development for testing, MMM, and multi-touch attribution (MTA). You will drive the strategic evolution of our data science initiatives, mentor a team of talented data scientists, and ensure that our methodologies remain cutting-edge. If you thrive in a fast-paced environment where you can both manage and build, this role is for you.

Responsibilities

  • Lead and mentor our lean data science team, fostering growth and technical excellence.

  • Own feature development for testing, MMM, and MTA models, ensuring methodological rigor and scalability.

  • Act as a hands-on contributor, developing statistical models and validating approaches for both testing and attribution.

  • Work cross-functionally with engineering and product teams to integrate data science solutions into Rockerbox’s platform.

  • Drive best practices in model validation, experiment design, and data pipeline efficiency.

  • Identify opportunities to leverage AI and machine learning for enhanced insights and automation.

  • Collaborate with leadership to define team growth, hiring needs, and strategic priorities.

Requirements

  • 7+ years of experience in data science, analytics, or machine learning, with at least 1-2 years in a leadership role.

  • Strong proficiency in Python, SQL, and cloud-based data platforms.

  • Deep understanding of statistical modeling, causal inference, and regression techniques.

  • Experience in feature development for MTA models and testing methodologies; experience with marketing data and consumer business KPIs.

  • Ability to hire, manage, and mentor data scientists while contributing as an IC.

  • Strong communication skills to effectively collaborate with engineers, product teams, and stakeholders.

Why You’ll Love Rockerbox: At Rockerbox, you’ll find a fast-paced, results-driven environment where your work has a direct impact on our growth and the success of our clients. Our iterative development process means you’ll see your contributions come to life quickly. You’ll join a supportive, light-hearted team that values collaboration and innovation. We are committed to professional growth and will actively support your development in both technical and business domains.

Benefits

  • Remote-first - work anywhere in the US

  • Health, vision, and dental insurance

  • Unlimited PTO

  • 10 Paid Holidays

  • Rockerbox Unplugged - we shut down the last week of the year

  • 12 weeks Parental Leave for all parents of a new child

  • Traditional and ROTH 401k options

  • $1000 annual training stipend

  • Rockertreat! Annual company get-together

Rockerbox is a remote-first, equal opportunity employer. We actively encourage applicants from underrepresented backgrounds, and we are accepting candidates based anywhere in the United States.

Please note that we are not able to accommodate C2C candidates for this role. Rockerbox participates in E-Verify. As an employer utilizing E-Verify, we confirm the eligibility of all newly hired employees through an electronic database maintained by the U.S. Department of Homeland Security and the Social Security Administration.

Top Skills

Cloud-Based Data Platforms
Python
SQL

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