Senior Data Scientist - Customer Experience at Coursera Sourcing
$132,000–$166,000from the description
Jul 22, 2026
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Jul 23, 2026
What this job asks for AI summary
A data science role embedded within a Customer Success function, focused on diagnosing shifts in customer metrics, building predictive models for churn and upsell, and applying causal inference to measure the impact of business initiatives. The work spans exploratory analysis, lightweight data pipeline work, dashboard support, and developing AI/LLM-based tools. Best suited to someone with broad applied data science experience who is comfortable bridging technical analysis and non-technical stakeholders.
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.
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 role is distributed/remote across specific US zones (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 posted salary range ($132,000–$166,000) corresponds to Zone 3–4 locations only; pay may differ for other zones not listed.
The JD requires a Bachelor's degree 'or higher' but also implies equivalent experience is acceptable given the framing; the degree requirement is set to None accordingly.
The 3–5 year experience range with scope limited to a single team (Customer Success) and no cross-org technical leadership supports a Mid-level classification despite the 'Senior' title.
dbt and Airflow are listed as examples of data pipelining tools under a 'working knowledge' qualifier, making them preferred rather than hard gates; Tableau and Sigma are similarly framed as examples of BI tools.
LLM/AI solution design is explicitly called out as a hard requirement ('Hands-on experience designing and deploying AI/LLM-based solutions') under the 'What You'll Have' section.
The alt SOC (15-2031 Operations Research Analysts) reflects the significant diagnostic analytics, KPI, and business-impact measurement work described, though the ML/modeling emphasis makes 15-2051 the stronger fit.
Read the full posting
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