Data Scientist - Marketplace Partnership

At Front Row, we partner with leading brands to accelerate their ecommerce growth. We leverage our capabilities and proprietary technology to design, market, distribute and accelerate brands on a global scale. We’re continually cultivating functional areas of expertise and retaining the highest caliber of talent — while sharing knowledge and data, creating efficiencies, and looking at every aspect of our client’s business from a 360 perspective. We work effectively to give every client the hands-on support, niche knowledge, and first-access they need to win in the world’s most competitive commerce markets and make each of our six capabilities the first to act on the next big things.

We live for the exchange of energy between brands and audiences, you should too, and we’ve made it our mission to expand every brand’s market share and heart share. Because we believe every transaction has the potential to be transformational. 

We leverage data-driven insights from Catapult, our proprietary technology, and our deep understanding of marketplaces like Amazon, Walmart.com, TikTok Shop, to craft strategies unique to each brand we work with while protecting their pricing and channel strategies at every lifecycle stage and in any global market.

Intro:

As a Data Scientist who thrives at the intersection of data architecture, data science, privacy-preserving technologies (including data clean rooms), and product development. In this role, you will go beyond traditional modeling and analytics to design scalable data systems, integrate clean room environments, and help shape data-powered products from inception to launch. You will work closely with software engineers, product managers, and cross-functional teams to architect robust data flows that power impactful customer-facing and internal products.

Description:

Data Architecture: Design, develop, and optimize scalable, reliable, and secure data pipelines and architecture to support both exploratory analytics and production workloads.

Product Development: Collaborate with product and engineering teams to develop data-driven products and features, from early discovery to production deployment.

Experimentation & Measurement: Design and implement experimentation frameworks, KPIs, and causal inference strategies for product evaluation.

Data Governance & Quality: Contribute to data governance processes, data documentation, and quality controls to ensure data integrity across systems.

Scalable Modeling: Develop production-ready machine learning and statistical models that are integrated into data products and customer experiences.

Build and deploy statistical, machine learning, and optimization models directly into production systems.

Drive causal inference and experimentation design (A/B testing, synthetic control, uplift modeling) to evaluate product and feature impact.

Create end-to-end pipelines for feature engineering, model training, validation, deployment, and monitoring.

• Education: Masters Degree in Mathematics, Computer Science, or Data Science
• Experience: 3 years of experience in data science, data engineering, or analytics roles with exposure to production-grade systems.
• Strong statistical and machine learning foundations, including causal inference techniques.
• In-depth knowledge of data architecture concepts, including data modeling, pipelines (batch/streaming), and cloud platforms (AWS, GCP, or Azure).
• Proficiency in SQL, Python/R, and experience with modern data tooling (Airflow, Spark, dbt, or similar).
• Demonstrated experience working on data-driven products, from prototype to production.
• Strong communicator who can explain technical concepts clearly to engineers, product managers, and executives.

• Health, dental, and vision
• PTO
• Summer Fridays
• Wellness and commuter benefits
• Work with a fun, consultative team of experts
• Location - headquartered in SoHo, New York City with offices in San Diego, Hamburg and Bratislava

Salary range $150,000 - $175,000

Salary : $150,000 - $175,000