Offer summary

Qualifications:

Bachelor’s degree in Applied Mathematics, Statistics, Computer Science, Data Science, or related fields., Minimum of 3 years of relevant work experience, with advanced degrees substituting for some experience., Expertise in machine learning, statistical modeling, and data analysis, with proficiency in Python or R., Strong understanding of the life insurance industry or similar business domain..

Key responsibilities:

Collaborate with business leaders to understand their needs and translate them into measurable business goals.

Independently gather project requirements and manage project plans to ensure timely deliverables.

Conduct advanced data analysis and build predictive models using sophisticated techniques.

Communicate results effectively to both technical and non-technical stakeholders.

Job description

The work we do has an impact on millions of lives, and you can be a part of it.

We help protect our customers against life’s uncertainties. Regardless of where you work within the company, you’ll be helping provide protection and peace of mind when our customers need it most.

As a Senior Data Scientist, you will lead and collaborate with a multidisciplinary team to design and develop innovative analytical products and solutions using advanced techniques such as Machine Learning, Natural Language Processing, and Deep Learning. Your role will involve critical thinking, problem-solving, and developing novel approaches to complex business challenges. You’ll need to navigate ambiguity and adapt to changing business priorities.

Responsibilities & Essential Functions:

Strategic Collaboration: Work closely with business leaders and partners to deeply understand their needs and translate them into well-defined business goals and measurable success criteria.

Requirements Gathering: Independently gather requirements from relevant stakeholders for various projects, ensuring the necessary data is available for analysis. Develop comprehensive project plans, execute deliverables within agreed-upon timeframes, manage deadlines, and provide recommendations to address any issues.

Advanced Data Analysis: Conduct data mining on large datasets (both structured and unstructured). Build and evaluate predictive models using sophisticated techniques.

Modeling: Under minimal supervision, create and execute plans to build, implement, and maintain predictive models using available tools and programming languages.

Effective Communication: Present and communicate results to diverse audiences, including both technical and non-technical stakeholders.

Solution Deployment & Maintenance: Collaborate with different functional teams to deploy algorithms and develop processes and tools for monitoring model performance and data accuracy.

Team Contribution and Development: Take an active role in team meetings and contribute ideas for continuous improvement. Stay updated on the latest trends and technologies in the field of data science.

Requirements:

Education: Bachelor’s degree in Applied Mathematics, Statistics, Computer Science, Data Science, or related fields.

Experience: A minimum of 3 years of relevant work experience. Advanced degrees may be used as a substitute for some experience.

Technical Proficiency: Demonstrated expertise in machine learning, statistical modeling, and data analysis.

Proficiency in programming languages such as Python or R.

Data Handling: Experience working with large datasets, data preprocessing, and feature engineering.

Domain Knowledge: Strong understanding of life insurance industry or similar business domain

Project Management: Ability to independently manage projects, including scoping, planning, execution, and communication with stakeholders.

Communication Skills: Excellent verbal and written communication skills to present complex technical concepts to non-technical audiences.

Preferred Qualifications:

Advanced Degree: Master’s or PhD in a relevant field (Applied Mathematics, Statistics, Computer Science, etc.).

Industry Experience: Previous work in a similar role within the industry or related field.

Publication Record: Contributions to research, publications, or patents related to data science or machine learning.

Collaboration: Proven ability to collaborate effectively with cross-functional teams.

Software Development: Familiarity with software engineering practices, version control, and deployment pipelines.

Certifications: Relevant certifications (e.g., AWS Certified Machine Learning Specialty, Google Professional Data Engineer).

Employee Benefits:

We aim to protect the wellbeing of our employees and their families with a broad benefits offering. In addition to offering comprehensive health, dental and vision insurance, we support emotional wellbeing through mental health benefits and an employee assistance program. Work/life balance is important and Protective offers a variety of paid time away benefits (e.g., paid time off, paid parental leave, short-term disability, and a cultural observance day). The financial health of our employees is just as important as physical and emotional health. Some of the financial wellbeing benefits include contributions to healthcare accounts, a pension plan, and a 401(k) plan with Company matching. All employees are encouraged to protect their overall wellbeing by engaging in ProHealth Rewards, Protective’s platform to improve wellbeing while earning cash rewards.

Eligibility for certain benefits may vary by position in accordance with the terms of the Company’s benefit plans.

Accommodations for Applicants with a Disability:

If you require an accommodation to complete the application and recruitment process due to a disability, please email martina.winston@protective.com. This information will be held in confidence and used only to determine an appropriate accommodation for the application and recruitment process.

Please note that the above email is solely for individuals with disabilities requesting an accommodation. General employment questions should not be sent through this process.

We are proud to be an equal opportunity employer committed to being inclusive and attracting, retaining, and growing an inclusive workforce.

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