Customer Success Data Science Analytics with SQL and Tableau

Fintech Company

San Diego CA OR Mountain View, CA HYBRID (3 days onsite)  Prefer San Diego

Needed ASAP

Contract until 7/31/2027

2 Openings

Must work on W2

Customer Success Data Analytics Consultant Needed- 

Part of the customer success team-

First Opening

Will Support the Canada Space

Will help to understand how the Canada space is doing

AHT- average handle time- metrics

Manage Canada products

Must be curious about metrics- up and down and be able to explain

Must be comfortable in the stakeholder/facing space

Build Datasets and pipelines- Tableau

Guide experimentation through to read results

Strong SQL a must

Databricks a nice to have

Metrics needed to optimize experience

Second Opening

Help with reporting for calls that include upselling and cross selling

OAR- sales type activities

Campaigns

Customer calls in- upsell or cross sell- then outbound calls to customers

Data Reporting and Infrastructure Space

Build Reports- Tableau

SQL a Must

Databricks nice to have

Metrics needed to optimize experience

Customer Success Data Science | Smart Expert Growth & Retention

About the Role

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. You'll help identify opportunities, measure impact, and uncover new ways to create value.

You'll partner closely with Expert Operations, Product, and Marketing to turn data into decisions and determine where combining human expertise with a great customer experience delivers the strongest results.

If you're passionate about using data to uncover creative, high-impact solutions at the intersection of customer experience, analytics, and expert-driven growth, we'd love to hear from you.

Key Responsibilities

Identify Opportunities & Shape Strategy

• Determine where and how expert-driven engagement can create the most value for customers.
• Size addressable opportunities and identify underserved customer segments.
• Frame the right business and analytical questions before jumping to a solution.

Optimize Timing & Targeting

• Analyze customer journey and engagement signals to identify the best moments for experts to engage.
• Determine which customer segments are most likely to benefit.
• Build predictive models to improve targeting and engagement.

Experimentation & Causal Analysis

• Design and analyze A/B tests.
• Apply causal inference methods when clean randomization is not possible, including:
• Propensity score matching
• Difference-in-differences
• Synthetic control
• Measure the true incremental impact of expert engagement on customer outcomes.

Generate Insights & Recommendations

• Partner with Expert Operations and Product to turn data patterns into actionable ideas.
• Develop targeting rules and new approaches to expert engagement.
• Make practical recommendations even when complete data is not available.

Build Self-Service Reporting

• Define meaningful KPIs, including efficacy, incremental lift, and opportunity capture.
• Build standardized dashboards that allow stakeholders to track performance without relying on one-off reporting requests.

Qualifications

• 4+ years of experience in product analytics, marketing analytics, or applied data science.
• Experience with customer experience measurement, growth analytics, or expert/agent-assisted service models preferred.
• Advanced proficiency in SQL.
• Experience with big data technologies such as Databricks, Spark, Redshift, or BigQuery.
• Experience with BI tools such as Tableau, Qlik, or Dash.
• Strong understanding of A/B/n experimentation and causal inference.
• Experience with methods such as propensity score matching, difference-in-differences, and synthetic control.
• Strong business acumen and strategic thinking.
• Ability to turn an ambiguous business question into a testable hypothesis and measurement plan.
• Strong data storytelling and visualization skills.
• Ability to clearly communicate insights to non-technical stakeholders.
• Excellent communication skills and the ability to work independently within a defined contract scope.

Education

Bachelor's degree required in:

• Engineering
• Data Science
• Statistics
• Mathematics
• Computer Science
• Economics
• Or another related quantitative field

Master's degree preferred.

Key Skills to Look For

SQL | A/B Testing | Causal Inference | Product/Growth Analytics | Predictive Modeling | Customer Journey Analytics | Databricks/Spark/BigQuery/Redshift | Tableau/Qlik/Dash | Data Storytelling | Stakeholder Communication