Senior Data Scientist - Field Business Solutions

UL Solutions

Chicago (IL)

On-site

USD 100,000 - 130,000

Full time

4 days ago

Be an early applicant

Application generator

Turn this role into an interview — a resume and cover letter built around what this employer wants.

Get past ATS filters

Job summary

UL Solutions in Northbrook, IL seeks an experienced Senior Data Scientist who partners with business leaders to translate problems into analytics initiatives. You will lead discovery, define success metrics, and drive adoption of data-driven solutions across functions.

You will own end-to-end analytics from data assessment to modeling, validation, and deployment, building dashboards in Power BI or Tableau and communicating insights to executives for strategic decisions.

Qualifications

Bachelor's degree in a quantitative field.
7–10+ years in data science or analytics.
Proven ability partnering with senior leaders.
Lead discovery, requirements, and measurable outcomes.
Strong business acumen and stakeholder influence.
Advanced SQL and Python or R.
Power BI or Tableau for decision-oriented visuals.
Experience in Agile environments and Azure DevOps.
Excellent communication and presentation skills.

Responsibilities

Build trusted relationships with business leaders, functional teams, and subject matter experts to understand priorities, operating context, constraints, and decision needs.
Lead discovery sessions to frame ambiguous business challenges, identify root causes, define hypotheses, and determine where analytics or data science can create meaningful value.
Translate business needs into clear problem statements, success measures, business requirements, user stories, and analytical plans.
Challenge requests when the proposed solution does not address the underlying business problem and recommend a more effective approach.
Align stakeholders on scope, priorities, assumptions, dependencies, risks, and expected outcomes before development begins.
Own end-to-end analytics and data science initiatives from discovery and data assessment through modeling, validation, implementation, adoption, and outcome measurement.
Analyze large and complex datasets to identify patterns, drivers, anomalies, opportunities, and actionable insights.
Design, develop, and evaluate statistical, predictive, and machine learning solutions using methods appropriate to the business question.
Define evaluation criteria that include analytical performance, interpretability, operational feasibility, business impact, and risk.
Perform data profiling, cleansing, reconciliation, and validation to ensure analytical outputs are accurate, explainable, and fit for purpose.
Develop decision-support tools, analyses, dashboards, and prototypes using SQL, Python, R, Power BI, Excel, or related tools.