[Hiring] Senior Data Scientist @UL Solutions

Role Description

We are seeking an experienced Senior Data Scientist who excels at connecting business needs with data-driven solutions. The ideal candidate has a proven record of working directly with business leaders, leading stakeholder discussions, structuring ambiguous problems, and translating analytical findings into clear recommendations and measurable outcomes. This position requires strong data science and analytics expertise, but it is specifically designed for someone whose strengths extend beyond technical delivery to include business acumen, stakeholder influence, executive communication, and solution adoption. Candidates should be comfortable challenging assumptions, guiding decisions, and collaborating with data engineering and technology teams without being primarily focused on backend development.

Responsibilities

• Business Partnership and Problem Definition
  • 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.
• Analytics and Data Science Delivery
  • 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.
• Insight Communication and Influence
  • Synthesize complex analysis into clear business narratives, options, recommendations, and implications for executive and non-technical audiences.
  • Create effective visualizations and presentations that focus on decisions, business impact, tradeoffs, and recommended actions rather than technical detail alone.
  • Facilitate stakeholder reviews, resolve conflicting perspectives, and influence decisions using evidence and sound business judgment.
  • Communicate limitations, assumptions, uncertainty, and risks transparently so stakeholders can make informed decisions.
  • Partner with users to validate outputs, incorporate feedback, drive adoption, and confirm that delivered solutions address the intended business need.
• Delivery Leadership and Cross-Functional Collaboration
  • Manage analytical backlogs, priorities, user stories, acceptance criteria, and delivery progress in Azure DevOps within an Agile environment.
  • Coordinate with data engineering, application, product, and platform teams on data availability, solution design, implementation, and production readiness.
  • Provide analytical leadership without assuming primary ownership for backend platform engineering, pipelines, or infrastructure.
  • Mentor Data Scientists and Analysts in business problem framing, stakeholder engagement, analytical rigor, documentation, and insight communication.
  • Establish and promote best practices for reproducibility, model validation, documentation, governance, and responsible use of data and analytics.
  • Identify opportunities to improve processes, reporting, decision workflows, and the organization’s broader analytics maturity.

Qualifications

• Bachelor's degree in data science, Statistics, Mathematics, Computer Science, Analytics, Economics, Engineering, or a related quantitative field.
• 7 to 10+ years of experience in data science, advanced analytics, decision science, or a closely related role.
• Proven experience partnering directly with business leaders and senior stakeholders to solve complex business problems and influence decisions.
• Demonstrated ability to lead discovery, gather and document requirements, define measurable outcomes, and translate ambiguous needs into analytical solutions.
• Strong business acumen and the ability to connect analytical work to operational, customer, financial, or strategic outcomes.
• Advanced proficiency in SQL and Python or R for data preparation, exploratory analysis, statistical modeling, and machine learning.
• Strong foundation in statistical methods, experimentation, predictive modeling, model evaluation, and analytical interpretation.
• Advanced experience with Power BI, Tableau, or similar tools, including the ability to design clear, decision-oriented visualizations.
• Excellent written, verbal, presentation, facilitation, listening, influencing, and stakeholder management skills.
• Experience delivering work in Agile environments and using Azure DevOps or a comparable work management platform.
• Ability to manage multiple priorities, communicate delivery risks, and maintain quality in a cross-functional enterprise environment.

Preferred Qualifications

• Master's degree in Data Science, Analytics, Statistics, Business Analytics, Economics, or a related field.
• Experience developing business cases, defining KPIs, measuring benefits, or evaluating adoption and realized value.
• Experience with causal inference, forecasting, optimization, NLP, deep learning, or other advanced analytical techniques.
• Experience working with Salesforce data and reporting.
• Experience in business services, manufacturing, field operations, or another complex enterprise environment.
• Familiarity with cloud data platforms, data lakes, and modern enterprise analytics ecosystems.
• Experience mentoring analytical professionals and raising standards for stakeholder-facing delivery.

Core Competencies

• Business Problem Solving - Frames the right problem and connects analytical work to business decisions and outcomes.
• Stakeholder Leadership - Builds trust, manages expectations, resolves ambiguity, and influences across functions and levels.
• Analytical Judgment - Selects fit-for-purpose methods and balances rigor, interpretability, speed, and practicality.
• Executive Communication - Turns complex findings into concise narratives, recommendations, and clear choices.
• End-to-End Ownership - Maintains accountability from discovery through adoption and outcome measurement.
• Cross-Functional Collaboration - Works effectively with business, data engineering, technology, and delivery teams.
• Mentorship and Standards - Develops others and promotes quality, documentation, governance, and continuous improvement.
• Strategic Thinking - Identifies opportunities and helps shape a longer-term analytics roadmap aligned with business priorities.

What Success Looks Like

• Business stakeholders view the individual as a trusted analytical partner, not only a technical resource.
• Projects begin with clearly defined business problems, decision owners, success measures, and expected value.
• Analytical recommendations are understandable, actionable, and used in business decision-making.
• Solutions achieve stakeholder adoption and demonstrate measurable operational or strategic impact.
• Delivery is transparent, risks are raised early, and analytical outputs meet agreed quality and governance standards.
• Junior team members improve their ability to engage stakeholders, structure problems, and communicate insights.

Benefits

• Estimated salary range: $100,000 to $130,000 USD.
• Annual bonus compensation with a target payout of 10% of the base salary.
• Health benefits including medical, dental, and vision.
• Wellness benefits such as mental and financial health.
• Retirement savings (401K) commensurate with the standard rewards offered in each individual location or country.
• Paid time off including vacation (15 days), holiday and personal days (totaling 12 days), and sick time off (72 hours).

Company Description

UL Solutions has been pioneering change since 1894 and we’re still leading the way. From day one, we’ve blazed a trail protecting the planet and everyone on it. Our teams have influenced billions of products, plus services, software offerings and more. We break things, burn things and blow things up. All in the name of safety science.

This is more than a job. It’s a calling. A passion to use our expertise and play our part in creating a more secure, sustainable world today — and tomorrow. As a member of our safety science community, you’ll use your ideas, your energy and your ambition to innovate, challenge and ultimately, help create a safer world.

Everyone here is unique. But we’re also a global community, working together to help create a safer world. Join UL Solutions and you can connect with the brightest minds in the business, all bringing their distinct perspectives and diverse backgrounds together to deliver real change.

Empowering our customers to keep the world safe means thinking ahead. It means investing in training and empowering our people to learn and innovate. At UL Solutions, we help build a better future — one where everyone benefits.

Join UL Solutions to be at the center of safety. To learn more about us and the work we do, visit UL.com.