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Kemper logo
Kemper

A Fortune 500 company formerly known as Unitrin, Kemper is one of the nation’s leading insurers, with over $2.7 billion in annual revenue and $8 billion in assets. Unitrin, found

Data Scientist – Customer Experience

Location

United States

Posted

127 days ago

Salary

$160K - $200K / year

Seniority

Senior

Bachelor Degree6 yrs expEnglishPythonSQL

Job Description

Data Scientist – Customer Experience

Kemper

• Lead complex, multi-signal investigations (e.g., account takeover, automation, fraud rings, API abuse) and produce clear, actionable remediation plans. • Serve as the CX technical authority in escalations, guiding hypothesis formation, analysis strategy, and root-cause conclusions. • Translate customer context (risk tolerance, user base, operational constraints, compliance) into measurable detection and tuning objectives. • Identify emerging fraud patterns and cross-tenant trends; conduct quarterly intelligence briefs for customers and recommended mitigations. • Design and recommend detection strategies combining rules, features, and (where applicable) model-driven scoring to reduce fraud while controlling false-positive costs. • Develop reusable feature definitions and tuning approaches that can be applied across customers (not only one-off tenant fixes). • Partner with engineering and products to shape product roadmap priorities, improve explainability and investigation tooling (e.g., “why did this fire,” attribution, drill-down paths). • Define and own CX measurement systems: detection quality, false-positive impact, operational metrics, customer outcomes, and performance over time. • Lead offline evaluation and backtesting methodologies for fraud controls and customer configuration changes. • Drive experimentation practices (A/B where feasible, quasi-experimental, pre/post with controls) and ensure results are decision-grade. • Detect data drift and performance degradation signals; propose retraining triggers and/or mitigation plans in partnership with ML/Engineering. • Create “investigation packs” for R&D: evidence, root cause hypothesis, recommended technical changes, and measurable acceptance criteria. • Mentor and develop other DS/analysts on CX through playbooks, code reviews, investigation standards. • Partner with GTM teams to quantify customer value, communicate outcomes, and support renewals/expansions through data-backed narratives.

Job Requirements

  • 6+ years in data science / applied analytics roles with increasing scope and ownership; fraud/risk/identity/security experience strongly preferred.
  • Expert-level SQL and strong Python for analytics and production-grade analysis (testing, modularity, version control habits).
  • Experience operating in customer-facing environments, including executive communication and handling escalations with calm, credible technical leadership with proven ability to lead end-to-end analytical initiatives.
  • Deep competence in statistics and evaluation:
  • hypothesis testing, segmentation, regression/classification metrics
  • time series / anomaly detection concepts
  • experimental design and causal inference fundamentals
  • Bachelor's degree in a quantitative field required; advanced degree preferred (MS/PhD).
  • Hands-on experience with real-time decisioning systems, streaming/event-based analytics, and latency-aware detection constraints.
  • Familiarity with modern ML methods used in fraud: supervised classifiers, graph/ring detection approaches, anomaly detection, and model monitoring.
  • Experience deploying or operationalizing models (MLOps exposure), including monitoring, drift detection, and retraining governance.
  • Experience with identity/authentication ecosystems (MFA modalities, risk-based authentication, device intelligence, bot defense signals).

Benefits

  • Health insurance
  • Flexible work hours
  • Paid time off
  • Professional development opportunities

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