Job DescriptionCore 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
The pay range for this role is:
86,100 - 128,700 USD per year (Remote (United States))
