Temporal Technologies
Senior Data Scientist
United States (Remote) · Senior
Sponsorship not specifiedDetected 13 days ago
PythonSQLBigQueryAWSCloud PlatformsTemporalData EngineeringData ScienceStatisticsA/B TestingOnboardingCustomer SuccessExperimental DesignCommunication
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odds of building a lasting career here
40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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About the role
- This role sits at the intersection of Data, Product, Growth, and GTM.
- You will work deeply embedded within the Product and Engineering teams focused on PLG.
- Your focus will be illuminating the user journey from initial interest to fully adopted and all the steps in between.
Responsibilities
- Act as an embedded Data partner to Product, Design, and Engineering, helping shape strategy, product proposals, and experiments from the earliest stages.
- Build analytical frameworks across the full PLG journey from acquisition and activation through engagement, adoption, expansion, monetization, and durability
- Design and evaluate experiments and product changes, using matched comparisons, pre/post-intervention analysis, causal methods, and other appropriate techniques when conventional A/B testing is not practical.
- Build reusable datasets, metrics, dashboards, and analytical tools that reduce ad hoc work and make insights accessible to Product, Marketing, Sales, and leadership.
Requirements
- Partner with Engineering and Data Engineering to improve event instrumentation, data quality, and the analytical models required for reliable product analysis.
- Proficiency in SQL and Python for analysis, modeling, and automation.
- Experience with modern data platforms and query engines such as Athena, Presto/Trino, BigQuery, or Snowflake.
- You will bring deep knowledge and practical experience with statistical methods including matched comparisons, quasi-experimental methods, and uncertainty measurements to help overcome these constraints.
- You have a keen sense for when additional data or analysis could materially change a conclusion, and when it wouldn't.
- You apply analytical rigor while balancing what is functionally required to advance a project.
Company info
- Audit signals currently captured in the onboarding flow and recommend new instrumentation as needed
- Establish reporting and repeatable analysis for PLG experiments.
- Analyze user behavior after the first successful Activity or Workflow.
- Identify signals of production readiness and common points where users stall.
- Map feature-adoption paths across important product areas.
- A strong foundation in statistics, experimental design, causal reasoning, and quantitative analysis.
- Experience using product, behavioral, or event data to improve activation, engagement, retention, conversion, or expansion.
- Experience working with small samples, noisy signals, imperfect control groups, or environments where standard A/B testing is not always possible.
- Strong judgment in choosing methods that fit the decision, available data, and level of uncertainty.
- Experience with cohort analysis, funnel analysis, segmentation, predictive modeling, and supervised or unsupervised machine-learning methods.
- Ability to prototype quickly in notebooks and convert recurring analyses into reliable data products, models, or workflows.
- Familiarity with cloud and object-store technologies such as AWS S3.
- Experience building dashboards and reusable analytical assets in a modern business intelligence platform.
- Comfort working with evolving definitions, incomplete instrumentation, and trade-offs between analytical precision and decision usefulness.
- A results-oriented mindset and a record of translating analysis into product or business action.
- Strong communication skills, including the ability to explain methods, uncertainty, and recommendations in plain language.
- Curiosity about developer platforms, cloud infrastructure, usage-based products, and how customers adopt technically complex products.
- A collaborative approach and the ability to work effectively with Product, Engineering, Marketing, Sales, Finance, and Data partners.
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This listing is sourced directly from Temporal Technologies's careers page and normalized into a canonical job model.