Data Scientist

Job Description

Core Functions

• Serve as the embedded analytics partner to Product teams; define feature success
• metrics before launch and measure outcomes after.
• Design and execute platform experiments — page templates, form flows,
• merchandising treatments, search experience — including power analysis and preregistered
• success criteria.
• Deliver clear reads on whether launches performed, including negative results.
• Apply quasi-experimental methods where controlled tests are not feasible: stagedrollout
• cohorts, difference-in-differences, matched comparisons, holdouts.
• Produce the analysis behind OEM and enterprise dealer group business reviews,
• and present those findings in the meeting alongside Account Management and the
• Director, who own the relationships.
• Answer network-level OEM questions: dealer base performance against benchmark,
• lagging markets and their causes, digital program and co-op spend effectiveness.
• Build and validate predictive models: lead scoring, days-to-sell and inventory turn,
• renewal risk, market-level demand forecasting.
• Partner with Data Engineering to move models and pipelines into production.
• Build the cross-network benchmarks used by OEM and enterprise account teams.
• Partner with Marketing to produce original research for external publication —
• industry studies, benchmark reports, whitepapers — owning the methodology, the
• analysis and the accuracy of every figure.
• Serve as the technical author behind that work as it reaches a wider audience: sales
• enablement material, conference and webinar content, and press or analyst
• enquiries.
• Convert recurring analyses into dashboards, templates and documented pipelines.
• Escalate platform issues surfaced in client data to Product, including where the cause is DealerOn's.

Requirements

• 3–5 years in analytics, data science, or analytics consulting.
• Advanced SQL — complex analytical queries against a data warehouse, written and
• debugged unaided.
• Python or R, with pandas or dplyr and a statistical modelling library (statsmodels,
• scikit-learn, tidymodels).
• Experimentation and causal inference: test design, power analysis, and quasiexperimental
• methods where a clean test is unavailable.
• Applied predictive modelling with evaluation against real baselines.
• Experience embedded with product managers and engineers, working to their
• cadence.
• Experience presenting analysis directly to senior business stakeholders and
• defending it under questioning.
• BI tool fluency: Tableau, Power BI, Looker or similar.
• Effective use of AI coding assistants, with the judgment to verify their output.

Preferred

• SaaS, digital marketing, agency, or automotive retail experience.
• Familiarity with OEM digital programs, co-op, or tier-3 marketing.
• Marketing measurement depth: attribution, incrementality testing, media mix
• modelling, GA4.
• Analytics engineering practice: dbt, warehouse modelling, orchestration.
• Cloud warehouse experience: BigQuery, Snowflake, or Redshift.

Automotive experience is not required.

#LI-Remote

This position is open to US residents only.

The targeted salary range for this position is $86,100 - $128,700.

The posted salary range for this position may be adjusted based on job-related factors permitted by law, such as experience and training; internal pay equity; licensure and certifications; market factors; departmental budgets; and responsibility. Our Talent Acquisition Team will be happy to answer any questions.

Perks and Benefits:

Aside from the awesome people you will get to interact with on a daily basis, we offer a number of benefits, including:

• Medical, dental and vision insurance
• Company matched 401K plan
• Flexible PTO + Sick Leave
• 6 weeks paid Parental Leave
• 8 Paid National Holidays
• Company-paid basic Life Insurance
• Voluntary supplemental Life Insurance
• Voluntary long-term/short-term disability insurance
• Voluntary Pet Insurance
• Optional Healthcare/Dependent Care FSA Account

DealerOn is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We also participate in E-Verify (for more information, click here: E-Verify Participation and Right to Work). A successful candidate must pass a background check as a condition of joining the team.