Sr Decision Scientist

Fractal Analytics•Texas, TX

1d•$145,000 - $155,000

About The Position

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets; an ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner. Role Overview We are seeking a Senior Decision Scientist with deep expertise in Adobe Analytics and Clickstream Analytics to lead funnel analysis and workflow integration across our acquisition and onboarding processes. You will leverage Adobe Analytics and clickstream data to understand the complete member funnel — from prospect discovery through product acquisition — identify gaps and drop-off points at each stage, and connect workflows to optimize the end-to-end journey. This role is critical to improving acquisition efficiency by mapping, analyzing, and optimizing the multi-stage funnel through advanced digital analytics and behavioral data insights.

Requirements

5+ years hands-on experience with Adobe Analytics
Deep expertise in: custom variables, eVars, props, events, success metrics
Advanced skills: segments, virtual report suites, processing rules, classifications
Proficiency in pathing analysis, funnel analysis, flow analysis
Experience with Adobe Analytics API or data feeds for custom analysis
Ability to troubleshoot implementation issues and validate data quality
5+ years analyzing behavioral/event-level clickstream data
Experience with event stream data: JSON formats, session-level data, user behavior sequences
Ability to build funnels, flows, and behavioral segmentation from raw clickstream data
Proficiency in SQL or Python to parse and analyze clickstream data
Understanding of how clickstream data connects to business outcomes
SQL proficiency: Query databases, build custom datasets, conduct complex analysis
Data analysis & statistics: A/B testing, statistical significance, causality, experiment design
Data visualization: Tableau, Looker, Power BI, or similar; ability to communicate findings visually
Programming (Python, R, or similar): Data manipulation, statistical modeling, automation
Funnel & conversion thinking: Experience analyzing multi-stage acquisition funnels and optimizing conversion rates
Digital analytics: Understanding of web analytics, user behavior, digital marketing
Friction diagnosis: Ability to identify UX bottlenecks, technical issues, and process complexity
Workflow/systems understanding: Comfort understanding how digital systems connect to business processes
Intellectual curiosity; problem-solving mindset
Collaborative; works across product, marketing, operations, and tech teams
Action-oriented; moves from insight to recommendation quickly
Strong communication; translates technical findings for non-technical audiences

Nice To Haves

Financial services or insurance (preferred): Familiarity with member acquisition, onboarding, regulatory context

Responsibilities

Use Adobe Analytics to map the complete acquisition funnel: awareness → consideration → quote → application start → application completion → underwriting → product issuance
Leverage clickstream data to understand exact user pathways and behavioral sequences at each funnel stage
Define and measure conversion rates at each stage; identify largest drop-off zones
Create funnel visualizations and dashboards showing how prospects flow through each stage
Analyze abandonment patterns: Where do prospects exit the funnel? What pages/interactions precede abandonment?
Use Adobe Analytics pathing analysis to identify common user paths before abandonment
Conduct clickstream analysis to find behavioral bottlenecks: time spent, re-attempts, error patterns
Quantify impact: How many members lost due to each friction point? What's the revenue impact?
Understand digital workflows at each funnel stage; map where prospects transition between stages
Identify friction points at stage boundaries: unclear CTAs, form complexity, technical errors, validation failures
Use Adobe Analytics and clickstream to diagnose: Is the drop-off due to technical issues, user confusion, or abandonment?
Build insights on which user segments/behaviors are most likely to drop off at each stage
Build Adobe Analytics segments to analyze funnel performance across prospect segments (new vs. returning, device type, referral source, demographic)
Use clickstream data to create behavioral segments: high-intent vs. low-intent, fast-movers vs. cautious explorers
Compare conversion rates and drop-off patterns across segments
Identify which segments and behaviors predict success vs. abandonment.
Design multi-touch attribution models in Adobe Analytics to understand which interactions drive conversion
Analyze how different funnel stages contribute to overall acquisition success
Understand the role of digital interactions vs. other touchpoints in member acquisition
Build Adobe Analytics dashboards showing funnel health: stage-by-stage conversion, abandonment rates, traffic mix
Create real-time dashboards for funnel monitoring; alerts for anomalies or degradation
Design clickstream-based dashboards showing user behavior patterns and flow paths
Provide actionable insights through data visualization
Translate Adobe Analytics and clickstream insights into prioritized recommendations
Design A/B tests to validate friction-reduction hypotheses; measure impact using Adobe Analytics
Quantify ROI: "If we reduce form complexity at Stage X, we expect Y% conversion lift worth $Z"
Prioritize recommendations by impact × feasibility