Data scientist iii

Description and Requirements

Work Location: Hybrid, 3 days onsite per week

Position Type: Contract, 10 months (potential for extension)

Location: Mountain View (preferred) or San Diego, California, USA

Compensation Range: $ per hour USD

Our Fortune 500 client is seeking a Data Scientist III. We are seeking a highly motivated Contractor Data Scientist to join our Customer Success Data Science team, focused on Smart Expert Growth and Retention. In this role, you'll be the analytical backbone for understanding how our consumer and expert experiences work together to drive the best possible outcomes for customers — from identifying opportunity, to measuring impact, to uncovering new ways to create value. You'll partner closely with expert operations, product, and marketing to turn data into decisions, and to prove out where combining human expertise with great customer experience delivers the best results. If you're passionate about using hard data to uncover creative, high-impact solutions at the intersection of customer experience and expert-driven growth, we'd love to hear from you!

Responsibilities

• Identify Opportunity & Shape Strategy: Bring strategic thinking to where and how expert-driven engagement can create the most value for customers — sizing the addressable opportunity, spotting underserved segments, and framing the questions worth answering before jumping to a solution.
• Identify Optimal Timing & Targeting: Analyze customer journey and engagement signals to determine the best moments and segments for experts to engage, and build predictive models to flag which customers are most likely to benefit.
• Run Experiments & Causal Reads: Design and analyze A/B tests, and apply causal methods (propensity matching, diff-in-diff, synthetic control) when clean randomization isn't feasible, to isolate the true impact of expert engagement on outcomes.
• Generate Ideas & Recommendations: Partner with expert operations and product to turn data patterns into new ideas, targeting rules, or expert engagement approaches — providing actionable recommendations even when complete data is unavailable.
• Build Self-Serve Reporting: Define KPIs (efficacy, incremental lift, opportunity capture) and build standardized dashboards so stakeholders can track performance without one-off requests.

Requirement:

• 4+ years of experience in product analytics, marketing analytics, or applied data science — ideally with exposure to customer experience measurement, growth analytics, or expert/agent-assisted service models
• Advanced proficiency in SQL and "big data" technologies (e.g., Databricks, Spark, Redshift, BigQuery); comfort with a BI tool (Tableau, Qlik, Dash)
• Solid grounding in experimentation design (A/B/n) and causal inference methods (propensity score matching, diff-in-diff, synthetic control) — including comfort applying these when clean experiments aren't feasible
• Strong business acumen and strategic thinking — able to translate a fuzzy business question into a testable hypothesis and measurement plan
• Strong data storytelling skills — able to rapidly build clear visualizations and communicate insights to non-technical stakeholders
• Excellent communication skills, with the ability to work independently against a defined scope typical of a contract engagement
• Bachelor's degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, Economics, or related quantitative field; Master's preferred

All interested applicants who meet the qualifications listed above are invited to submit a resume by clicking "Apply Now". The indicated pay range for this position is a good‑faith estimate based on the qualifications necessary for the position, including experience, training, and other considerations permitted by law. The pay band is established by the client company. Factors that may influence an offer include a candidate’s skills, experience, geographic location, and expected work quality and quantity. Most candidates will start in the lower half of the pay range, with the upper end reserved for those with extensive experience and skills or who live in higher‑pay markets. An employee’s pay history will not be considered where prohibited by law. This information is subject to change and serves as a general guideline for compensation discussions. Actual offers may vary based on specific circumstances and company policies.