Lead Marketing Data Scientist

About One Park Financial

One Park Financial is a leading fintech company empowering small and medium-sized businesses across the United States with fast, flexible access to working capital. Operating in a high-growth, performance-driven environment, we leverage data, technology, and an entrepreneurial culture to connect business owners with the funding solutions they need to thrive.

Position Overview

We are looking for a Lead Marketing Data Scientist to architect, streamline, and optimize the data flows that connect our marketing platforms to our core business metrics. This role sits at the intersection of marketing, data engineering, and growth strategy, and is responsible for building the analytical foundation that drives smarter media investment decisions across the organization.

The Lead Marketing Data Scientist will own end-to-end Marketing Mix Modeling (MMM), incrementality testing, geo-lift experimentation, and scenario analysis frameworks. The insights produced will directly influence how One Park Financial allocates millions in marketing spend, with the ultimate goal of driving and surpassing revenue, funding volume, and customer acquisition targets.

This is a high-impact, high-visibility role for a senior practitioner who thrives in fast-paced, data-rich environments and is energized by translating impression- and click-level signals into business outcomes.

Key Responsibilities

Data Architecture & Integration

Design, streamline, and integrate data pipelines between marketing platforms (Google Ads, Meta, TikTok, LinkedIn, programmatic DSPs, affiliate networks, CRM, call tracking) and the business data warehouse.

Build and maintain a unified marketing data layer that connects impressions, clicks, and engagement signals to downstream conversion, funding, and revenue events.

Partner with Data Engineering to define schemas, ingestion patterns, and data quality standards that ensure trusted, decision-grade marketing data.

Continuously identify and eliminate gaps, latency, and inconsistencies between platform-reported metrics and business outcomes.

Marketing Mix Modeling & Scenario Analysis

• Develop, productionize, and own the company’s Marketing Mix Modeling (MMM) framework across paid, owned, and earned channels.
• Run scenario analyses and budget optimization simulations to recommend optimal media mix under varying spend, seasonality, and macroeconomic conditions.
• Quantify diminishing returns, saturation curves, carryover effects, and channel interactions to inform short- and long-term planning.
• Translate model outputs into clear, actionable recommendations for marketing leadership and the executive team.

Incrementality, Geo-Lift & Experimentation

• Design and execute geo-lift studies, holdout tests, and matched-market experiments to measure true incremental impact by channel and campaign.
• Establish a rigorous experimentation roadmap and testing cadence across the media portfolio, including paid social, paid search, display, CTV, audio, and direct mail.
• Reconcile platform-attributed performance with incrementality results, and educate stakeholders on the difference between correlation and causal impact.

Performance Insights & Business Impact

• Correlate impression- and click-level signals with funded loans, revenue, LTV, and other core business KPIs.
• Build self-serve dashboards and analytical products that help the marketing organization make confident, data-driven media mix decisions.
• Surface growth opportunities, efficiency gains, and underperforming investments through proactive analysis and storytelling.
• Set and track measurement standards, attribution conventions, and success metrics across the marketing organization.

Leadership & Cross-Functional Partnership

• Serve as the technical and analytical thought leader for marketing measurement across the company.
• Partner closely with Performance Marketing, Brand, Finance, Product, and Data Engineering teams to align measurement with business strategy.
• Mentor analysts and junior data scientists, and help shape the long-term marketing analytics roadmap and team structure.
• Communicate complex statistical concepts and trade-offs clearly to non-technical executives and channel owners.

Requirements

• 7+ years of experience in data science, marketing analytics, or quantitative marketing, with at least 3 years focused on performance marketing measurement.
• Experience working with AWS in Cloud data platform.
• AI/ML based LTV prediction experience to build predictive models that help achieve business outcomes.
• Proven track record of building and deploying Marketing Mix Models (MMM): Bayesian (e.g., Robyn, Meridian, LightweightMMM, PyMC) or frequentist in production environments.
• Hands-on experience designing and analyzing incrementality tests, geo-lift studies, and causal inference experiments (synthetic control, difference-in-differences, uplift modeling).
• Strong programming skills in Python (pandas, NumPy, scikit-learn, statsmodels, PyMC / Stan) and SQL; comfortable working with large-scale datasets.
• Deep, hands-on experience with at least one major cloud data platform (Snowflake, BigQuery, Databricks, Redshift) and modern data stack tooling (dbt, Airflow, Fivetran, or equivalent).
• Strong working knowledge of digital media and performance platforms including Google Ads, Meta Ads, programmatic DSPs, affiliate platforms, call tracking, and attribution tools.
• Experience operating in a SaaS, fintech, financial services, or other fast-paced, high-growth, performance-driven environment.
• Excellent communication and storytelling skills with the ability to influence senior stakeholders and translate analytics into business action.
• Bachelor’s degree in a quantitative discipline (Statistics, Economics, Mathematics, Computer Science, Engineering, or related field).

Preferred Qualifications

• Master’s or Ph.D. in Statistics, Econometrics, Data Science, or related quantitative field.
• Experience in financial services, lending, small business finance, or other regulated industries.
• Familiarity with privacy-aware measurement approaches (data clean rooms, conversion APIs, server-side tracking, MMM in a post-cookie world).
• Experience integrating LTV, retention, and unit-economics models into marketing measurement frameworks.
• Exposure to visualization tools such as Looker, Tableau, Power BI, or Streamlit for analytical product delivery.
• Prior experience leading or mentoring a team of analysts or data scientists.

Benefits

What We Offer

• Competitive base salary plus performance-based bonus.
• Comprehensive health, dental, and vision insurance.
• 401(k) plan with company match.
• Hybrid / flexible work environment.
• High-visibility role with direct impact on company strategy and growth.
• Collaborative, entrepreneurial culture with significant opportunity for career advancement.

Equal Opportunity

One Park Financial is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.