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Data Science Specialist II

4 months ago

McKinney, United States Globe Life Inc. Full time


Data Science Specialist 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 Manager 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 predictive models and monitoring tools
    • Applies mathematical, statistical, and quantitative techniques to draw conclusions, make recommendations, and drive change
    • Performs and helps guide clustering and / or segmentation analysis
  • Data / Analysis:
    • Aids in identifying and utilizing new data sources (data exploring, cleaning, and wrangling)
    • Maintains and shares knowledge of data analysis tools, data visualization, developing analysis queries and procedures in SQL, BI tools, or other analysis software
  • Projects:
    • Understands the business direction and follows the Data Science COE roadmaps and priorities to influence business and drive improvements
    • Manages personal time and assists others to ensure projects are completed and delivered on time
    • Outlines, performs, and coordinates 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 and identify areas where data science can drive value
    • Communicates project progress, updates, and results to stakeholders and 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:
    • Expert skills in mathematical and statistical techniques to foster fact-based decision-making
    • Efficient feature engineering and selection (i.e., data manipulation, variable derivation, transformation, data classification)
    • Aware of data governance and data management practices
  • 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
  • Industry:
    • Experience working in the insurance industry, or a related field, is preferred
    • Familiarity with data privacy and security regulations
  • Languages / Tools / Environments:
    • Experience with many 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)
      • Machine learning services (e.g., SageMaker, DataRobot)
    • Modeling:
      • 4+ years of experience in data science and machine learning, including experience with popular data science tools and programming languages
      • Firsthand work 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)
    • Projects:
      • Project management experience, including leading individual projects through the data science life cycle
  • Schedule:
    • Onsite or Hybrid (WFH/Remote - Monday and Friday) & (In Office - Tuesday thru Thursday)

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