Senior Data Scientist - Customer Experience
Coursera
$132,000–$166,000from the description
Jul 22, 2026
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Jul 23, 2026
What this job asks for AI summary
A senior individual-contributor data science role embedded within an Enterprise Customer Success function, focused on reducing churn and supporting revenue growth. Day-to-day work spans exploratory analysis, predictive modeling (churn and upsell forecasting), causal inference, and lightweight data pipeline work, with close collaboration with non-technical Customer Success stakeholders. Suits someone with 3–5 years of applied data science experience who is comfortable moving across SQL, Python, and BI tooling independently.
Mid level · 3+ years · Remote · Full-time
Advertised as Senior, but the requirements read as Mid.
“or” means any one of them counts — you don't need all of them.
Posted 2 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 5,100 people nationally plausibly meet what this posting asks for (data scientists). range 3,050–7,600
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
The advertised title is 'Senior Data Scientist', but the stated experience requirement of 3–5 years and the scope of work (team-level analytics support, no org-wide technical authority) align more closely with a Mid-level role.
The degree requirement states 'Bachelor's degree or higher' but frames it as a baseline alongside equivalent experience context; however, the JD does not explicitly offer an experience-in-lieu-of-degree substitution, so the degree requirement is set to None as a conservative read given the 'or higher' framing and quantitative-discipline focus.
dbt and Airflow are listed together as interchangeable examples of 'data pipelining tools' under a 'working knowledge' qualifier in the requirements section, so they are captured as alternatives of each other and marked preferred.
Tableau and Sigma are listed as interchangeable BI tool examples under 'working knowledge' in the requirements section; marked preferred accordingly.
Forecasting and regression appear as named statistical methods within the requirements block but are supporting techniques rather than standalone technology gates; included as preferred to reflect their secondary framing.
The compensation range ($132,000–$166,000/year) is labeled 'US Zone 3–4', covering states such as CA (outside SF Bay Area), CO, CT, DC, GA, IL, MA, MD, NY/NJ (outside NYC Metro), OR, RI, TX, VA, and WA (outside Seattle Metro). No single CBSA applies; the role is distributed/remote across these zones.
The role is on the Enterprise CX / Customer Success team, giving it a meaningful BI/analytics flavor; the alternative occupation 15-2031 (Operations Research Analysts) is noted as a runner-up given the heavy diagnostic and business-analytics orientation alongside the ML/modeling work.
Read the full posting
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