2U
higher education
DataScientistII
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Scientist II at 2U. Skills: Product analytics, Experimentation, Causal inference, Data modeling, Machine learning. Product analytics and ad hoc analysis. Serve as the analytics partner for Product, Marketing, and Finance teams”
What You'll Achieve.
Drive insight and decision-making for edX.org; Reduce the long tail of repeat requests
Industry & Context.
Excited by ambiguous business problems; Triage a high volume of stakeholder requests and match each one to an appropriate level of rigor; Skilled at turning messy data into clear, actionable insight
Prioritize candidates who live in the Washington-Baltimore metropolitan area, Available to come into Headquarters in Arlington, VA two days a week
What They're Looking For.
Must Have
Bachelor's degree in a quantitative field (data science, statistics, mathematics, computer science, economics, or similar), 3–5 years in data science, product analytics, or a related quantitative role, Solid foundation in hypothesis testing, power analysis, confidence intervals, and multiple comparisons, EDA and validation skills on unfamiliar data, Running A tests end-to-end, Python (pandas, NumPy, scikit-learn), Advanced SQL on large, complex datasets
Nice to Have
Graduate degree preferred, Experience with modern experimentation platforms (e.g., Statsig, Eppo, Optimizely, LaunchDarkly), Hands-on with platforms like Amplitude, FullStory, or Mixpanel, Prior work in EdTech, online learning, or a comparable consumer subscription / marketplace product, Exposure to large-scale data platforms (e.g., Snowflake, BigQuery, Databricks, Spark)
What You'll Do.
Product analytics and ad hoc analysis
Serve as the analytics partner for Product
and segmentation work
Triage a high volume of incoming requests
Own A tests end-to-end
from design and power analysis through interpretation
Use quasi-experimental methods where randomization isn't possible
Establish and maintain north-star
Build scalable dashboards and tooling
Partner with Data Engineering to keep upstream sources trustworthy
Contribute to dbt models
Lead EDA on unfamiliar datasets
Add checks that catch quality issues
Use standard ML techniques (classification
Develop a deep understanding of the edX product
Coach partners on statistical concepts
Refine ambiguous questions
Turn complex findings into actionable recommendations
How You'll Work.
Team & Collaboration
Partner with Product, Marketing, and Finance stakeholders; Partner with Data Engineering
Communication Scope
Able to refine ambiguous questions; Translate findings for business partners; Clarify what the results do and don't say; Communicates complex findings in ways that educate and enable stakeholders
Full Job Description
At 2U, we are all in on purpose. We are motivated by our mission – to make learning limitless– and connected by our shared passion to deliver world-class higher education at scale. As the parent company of edX, a leading online learning platform, 2U powers thousands of higher education offerings – from free courses to full degrees. Together with our college, university, and corporate partners, we are helping accelerate careers and transform lives. What We’re Looking For: The Data Scientist II will partner with Product, Marketing, and Finance stakeholders to drive insight and decision-making for edX.org, 2U's open online learning marketplace. This is a high-leverage analytics role focused on product analytics, experimentation, and causal inference on large, complex behavioral datasets. We are looking for someone who is excited by ambiguous business problems, can triage a high volume of stakeholder requests and match each one to an appropriate level of rigor, and is skilled at turning messy data into clear, actionable insight. The ideal candidate is intellectually curious, takes the initiative to understand the domain and refine the question behind the question, and communicates complex findings in ways that educate and enable stakeholders. Responsibilities Include, But Are Not Limited To: Product analytics and ad hoc analysis Serve as the analytics partner for Product, Marketing, and Finance teams on edX.org, delivering funnel, cohort, retention, and segmentation work. Triage a high volume of incoming requests and match the depth of each response to the decision at hand, from back-of-the-envelope estimates to deeper investigations. Experimentation and causal inference Own A/B tests end-to-end, from design and power analysis through interpretation. Where randomization isn't possible, use quasi-experimental methods such as difference-in-differences, propensity scoring, regression discontinuity, and synthetic control. Metric definition and self-serve enablement Establis
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