Data Science Analyst II (Hybrid)

Job Description

Data Science Analyst II (Hybrid)

Primary Duties & Responsibilities

JOB SUMMARY:

Experience what being part of the Globe Life family feels like. Be inspired by your leaders, encouraged, and cheered on by your teammates to excel and be supported in your career while working with us. We offer a competitive salary with a great benefits package, including 401(K) match, medical, dental, and vision health plans, short – term and long-term disability, paid time off, tuition reimbursement and other career development opportunities.

The Actuarial Department is responsible for supporting and enhancing sustainable growth of both sales and profits while managing the risks and safeguarding the solvency of Globe Life. Actuaries are involved in life and health insurance product design, development, pricing and implementation, and are instrumental in the ongoing financial management of the enterprise.

This position reports to the Director of Data Science within the Actuarial department and is responsible for a full range of activities related to data analysis, modeling, planning, development, deployment, and support of new and existing projects impacting multiple businesses units and business processes.

PRIMARY DUTIES & REPONSIBILITIES:

• Models:
  • Designs, develops, and implements data pipelines, predictive models, and monitoring tools
  • Applies mathematical, statistical, and quantitative techniques with guidance to draw conclusions, make recommendations, and drive change
  • Works with team members to perform clustering and / or segmentation analysis
• Data / Analysis:
  • Aids in identifying and utilizing new data sources (data exploring, cleaning, and wrangling)
  • Develops knowledge of data analysis tools, data visualization, developing analysis queries and procedures in SQL, BI tools, or other analysis software
• Projects:
  • Acquires an understanding of the business direction and follows the Data Science COE roadmaps and priorities to influence business and drive improvements
  • Manages personal time to ensure projects are completed and delivered on time
  • Performs analytical tasks which include the evaluation of the business problem, analytical methodology, prototypes, validation, documentation and presentation of findings and recommendations
  • Adheres to risk and compliance policies, standards, and procedures for business activities
• Collaboration / Communication:
  • Collaborates with team members, business stakeholders, and subject matter experts to understand data needs and assist in areas where data science can drive value
  • Communicates individual project progress to leadership on a regular basis

Required Skills

KNOWLEDGE, SKILLS, & ABILITIES:

• Communication:
  • Effective communication skills, including the ability to explain complex technical concepts to non-technical stakeholders with data, dashboards, and visualizations
• Modeling:
  • Solid skills in mathematical and statistical techniques to support fact-based decision-making
  • Awareness of feature engineering and selection (i.e., data manipulation, variable derivation, transformation, data classification)
• Development:
  • A passion to learn, assist others, build relationships, and a growth mindset.

Applicable to all employees of Globe Life & Accident and its subsidiaries:

• Reliable and predictable attendance of your assigned shift
• Ability to work full time and/or part time based on the position specifications.

Required Knowledge & Experience

EDUCATION & WORK EXPERIENCE REQUIRED:

• Education:
  • Bachelor’s degree or equivalent experience in a relevant field such as Economics, Statistics, Mathematics, Actuarial Science, and/or Data Science
• Languages / Tools / Environments:
  • Experience with any of the following categories is preferred:
    • Programming / scripting languages (e.g., Python, R)
    • SQL and relational databases (e.g., SQL Server)
    • Data visualization tools (e.g., Tableau)
  • Modeling:
    • Experience in data science and machine learning, including experience with popular data science tools and programming languages is preferred
    • Firsthand work or educational experience analyzing large, complex data sets and developing supervised and unsupervised machine learning algorithms (e.g., regression, decision trees/random forest, gradient boosting, feature selection/reduction, clustering, parameter tuning)
• Schedule:
• Onsite or Hybrid (WFH/Remote – Monday and Friday) & (In Office – Tuesday thru Thursday)