Data Scientist

UL Solutions; Melville (NY); On-site; USD 80,000 - 120,000; Full time

Benefits offered by this job

Salary: $80,000 to $120,000

Annual bonus of 10%

Health benefits: medical, dental, vision

401(k)

15 days vacation, 12 floating holidays, 72 hours sick time

Job summary

UL Solutions is hiring a Data Scientist in Melville, New York, to deliver insights through data analysis. You will collaborate with stakeholders, build visualizations, and develop predictive models, ensuring high-quality data for analysis.

The ideal candidate will have a Master’s degree in Data Science and 3–5 years of experience, with strong proficiency in SQL, Python, and data visualization tools like Power BI.

Qualifications

• 3–5 years of experience in data analytics or data science roles.
• Strong proficiency in SQL, Python, R.
• Experience with Power BI, Tableau or similar visualization tools.
• Understanding of statistical methods and probability theory.

Responsibilities

• Process, cleanse, and verify the integrity of data for analysis.
• Analyze large datasets to extract meaningful insights.
• Build and maintain dashboards using Power BI or Tableau.
• Collaborate with business and technical stakeholders.

Skills

SQL

Python

R

Data visualization with Power BI

Machine learning techniques

Statistical analysis

Problem-solving

Agile methodologies

Education

Master’s degree in Data Science, Data Analytics, or related field

Tools

Tableau

Azure DevOps

Job description

Job Description The Data Scientist is responsible for delivering data-driven insights and analytical solutions that support business decision-making. This role partners closely with business stakeholders, data engineering, and development teams to analyze complex datasets, build visualizations, and develop predictive models. The ideal candidate combines strong analytical skills with business acumen and effective communication in an Agile environment.

Responsibilities

• Process, cleanse, and verify the integrity, quality, and reliability of data used for analysis, reporting, and predictive modeling.
• Perform ad‑hoc and recurring analyses, presenting results and insights in a clear, concise manner to support business decision‑making.
• Analyze large, complex datasets to extract meaningful insights, selecting appropriate statistical, analytical, and machine learning techniques based on the problem context.
• Select relevant features and build, evaluate, and optimize classification and predictive models using machine learning techniques.
• Apply data mining and advanced analytical methods to identify trends, patterns, and relationships within structured and unstructured data.
• Extend and enrich customer and business datasets using third‑party data sources when required to improve analytical outcomes.
• Enhance data collection and preparation procedures to ensure relevant, high‑quality inputs for analytic and machine learning systems.
• Use data modeling and evaluation strategies to identify patterns and accurately predict unseen or future instances.
• Collaborate with business and technical stakeholders to align analytical solutions with business objectives.
• Adhere to the Underwriters Laboratories Code of Conduct and follow all physical and digital security, data governance, and compliance practices. Collaborate with business stakeholders to gather, analyze, and document requirements, translating needs into BRDs, user stories, and functional specifications.
• Analyze large, complex datasets using statistical and analytical techniques to identify trends, patterns, and actionable insights.
• Build and maintain dashboards, reports, and data visualizations using Power BI, Tableau, or similar tools.
• Apply statistical methods and basic machine learning models to support forecasting, prediction, and business decision‑making.
• Perform ad‑hoc and recurring analyses to support both operational reporting and strategic initiatives.
• Process, cleanse, validate, and maintain data accuracy and integrity across analytical datasets.
• Enhance data collection processes and integrate third‑party data sources to improve analytical coverage and model performance.
• Communicate analytical findings and recommendations clearly to both technical and non‑technical audiences.
• Partner with development teams using Azure DevOps to manage work items, track progress, and ensure timely delivery.
• Support data science and analytics initiatives using SQL, Python, R, and Excel.
• Collaborate with data engineering teams to support analytics pipelines and data lake initiatives.

Required Qualifications

• Master’s degree in Data Science, Data Analytics, Computer Science, or related field
• 3–5 years of experience in data analytics or data science roles
• Strong proficiency in SQL, Python, and R
• Experience with Power BI, Tableau, or similar visualization tools, including data modeling and DAX
• Strong analytical and problem‑solving skills with attention to detail
• Experience gathering and documenting business requirements
• Familiarity with Agile methodologies and Azure DevOps
• Excellent communication, interpersonal, and stakeholder management skills
• Understanding of statistical methods and probability theory

Preferred Qualifications

• Experience with machine learning frameworks such as scikit‑learn, TensorFlow, or Keras
• Experience with Salesforce data and reporting
• Experience in business services or manufacturing industries
• Familiarity with NLP or deep learning techniques

Benefits

Salary: $80,000 to $120,000. Eligible for annual bonus with target payout of 10% of base salary. Health benefits include medical, dental, vision, wellness support, and 401(k). Paid time off: 15 days vacation, 12 floating holiday days, 72 hours sick time.