Data Scientist

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.

• 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 Dev Ops 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.

• 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 Dev Ops
• Excellent communication, interpersonal, and stakeholder management skills
• Understanding of statistical methods and probability theory

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

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.