Senior Data Scientist Senior Data Scientist …

Brighthouse Financial, Inc.
in Charlotte, NC, United States
Self Employed, Full time
Be the first to apply
Competitive
Brighthouse Financial, Inc.
in Charlotte, NC, United States
Self Employed, Full time
Be the first to apply
Competitive
Senior Data Scientist
Brighthouse Financial is on a mission to help people achieve financial security. As one of the largest providers of annuities and life insurance in the U.S., we specialize in products designed to help people protect what they've earned and ensure it lasts. We are built on a foundation of experience and knowledge, which allows us to keep our promises and provide the value they deserve.

At Brighthouse Financial, we're fostering a culture where diverse backgrounds and experiences are celebrated, and different ideas are heard and respected. We believe that by creating an inclusive workplace, we're better able to attract and retain our talent, provide valuable solutions that meet the needs of our advisors and their clients, and deliver on our mission of helping more people achieve financial security. We're se eking passionate, high-performing team member to join us. Sound like you? Read on.

How This Role Contributes to Brighthouse Financial:
Data Scientists in Brighthouse Financial's Data Science organization work closely with cross--functional teams in marketing, distribution, actuarial, product and other functions, leveraging Brighthouse Financial's rich datasets to develop and deliver propensity models and data--driven insights, and ultimately drive Brighthouse Financial's top line growth. A successful candidate will be passionate about finding insights in data and using quantitative analysis to answer complex questions, with a collaborative and resourceful style.

Key Responsibilities:
  • Conduct data analytics with the relevant programming / statistical package (such as R or Python) for large-scale problem solving
  • Work independently and possesses exceptional technical ability.
  • Understand complex business challenges, develop hypotheses, convert into the right analytical hypothesis, and communicate the results back to the partner teams with limited or no analytical background to drive the business strategy
  • Analyze internal / external, online / offline, and structured / unstructured data such as speech analytics, digital footprints, financial information, proprietary market research and secondary sources to identify insights
  • Create innovative solutions to business problems.
  • Partner with other operational areas to identify opportunities for new projects.
  • Build strong working relationships and improve workflow and organizational issues.
  • Build complex advanced-level machine learning and advanced analytics models.
  • Handle and resolve questions and issues referred by junior staff members.
  • May propose, evaluate and implement process improvements to increase efficiency and effectiveness.
  • Perform other duties as required or assigned.

Essential Business Experience and Technical Skills:
  • Doctoral degree in a technical field and two plus years of related work experience, or a Master's degree in a technical field and at least 3-4 years of related work experience, or a Bachelor's degree in a technical field and at least 6-8 years of related work experience.
  • Significant professional experience required applying quantitative analysis and modeling to solving real-world business problems including experience in model validation, testing and deployment
  • Demonstrated proficiency in Python/PySpark required
  • Demonstrated ability to perform high quality work independently
  • Excellent oral and written communication skills, including the ability to explain complicated quantitative concepts to non--technical stakeholders using effective story telling techniques and visualization
  • Ability to translate business requirements into detailed analysis plans.
  • Ability to prioritize requests to meet the most important and urgent business needs
  • Working knowledge of insurance industry is a plus
  • Prior exposure to financial services or insurance industry preferred

Travel:
Less than 5%

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