Data Scientist II - CX Analytics

When you join the team at Unum, you become part of an organization committed to helping you thrive. Here, we work to provide the employee benefits and service solutions that enable employees at our client companies to thrive throughout life’s moments. And this starts with ensuring that every one of our team members enjoys opportunities to succeed both professionally and personally.

To enable this, we provide:
Award-winning culture Inclusion and diversity as a priority Performance Based Incentive Plans Competitive benefits package that includes:
Health, Vision, Dental, Short & Long-Term Disability Generous PTO (including paid time to volunteer!) Up to 9.5% 401(k) employer contribution Mental health support Career advancement opportunities Student loan repayment options Tuition reimbursement Flexible work environments All the benefits listed above are subject to the terms of their individual Plans. And that’s just the beginning… With 10,000 employees helping more than 39 million people worldwide, every role at Unum is meaningful and impacts the lives of our customers.

Whether you’re directly supporting a growing family, or developing online tools to help navigate a difficult loss, customers are counting on the combined talents of our entire team. Help us help others, and join Team Unum today!

We are seeking a Data Scientist II to join the CX Analytics team within our Customer Experience Organization. Our team leverages AI across development workflows and uses it to extract insights from both structured data and unstructured sources such as raw text, and you will apply these capabilities in your day-to-day work. In this role, you will focus on executing applied data science work—running analyses, supporting experiments, and mining data to uncover drivers and patterns that inform how the business supports its customers.

You will work across structured and unstructured data to answer complex business questions and contribute to larger analytical efforts that connect findings to outcomes across BI/reporting, operations, and value stream partners. You will operate with a solid degree of independence on moderately complex work, partnering closely with BI Analysts and Data Engineers to ensure analyses are grounded in reliable data and effectively operationalized.

The ideal candidate is a strong analytical thinker and collaborator who can dig into data, apply the right techniques to the problem at hand, and consistently turn analysis into meaningful insights that support better decision-making across the organization. This is a campus-based role. Current remote and field-based Unum employees may apply and will be considered in accordance with company policy.

• Design and execute analytical solutions using optimization, simulation, data mining and other statistical methods with a focus on delivering actionable business value.
• Integrate large volume of data from different sources (including DB2, SQL Server, Web API and Teradata) to create data assets for ad-hoc analyses and larger studies.
• Apply validation, aggregation, and reconciliation techniques to create rich modeling-ready data framework.
• Construct and tune predictive models to explain and understand observed events, forecast expected behavior, or identify risk through scoring or clustering.
• Efficiently interpret results and communicate findings and potential value to influence manager and leadership decision making.
• Support integration of solutions within existing business processes using automation techniques.
• Understand theory and application of current and emerging statistical methods and tools.
• Provides support, training and/or mentorship to lower-level Data Science peers.
• Perform other related duties as assigned

Bachelor’s degree in quantitative field is required, Master’s is preferred 4 years of professional experience or equivalent relevant work experience preferred

• Deep expertise in at least two of the following skillsets preferred; and competency in the other:
  Programming & Process automation:
  Experience with file I/O, database integrations, and APIs to build automated analytics pipelines. Understanding of process research and design, which may be demonstrated through use of Dev Ops, automation, data mining, web scraping, or object-oriented software is preferred.
• Data Visualization:
  Expertise on at least one visualization tool with working knowledge of others and expertise in static data visualization. Understanding of dynamic data visualization.
• Statistics & Statistical modeling:
  Expertise using statistical inference and regression. Solid understanding of machine learning algorithms. Solid understanding of feature selection and extraction. Conducts end-to-end machine learning tasks from problem synthesis to model deployment.
• Data Extraction, Transformation, and Loading:
  Preferred skills include expertise in writing complex SQL queries that join multiple…