Travelers
Data Science Leadership Development Program (DSLDP) Sr. Associate Data Scientist
CT - Hartford, USA · Senior · Full-time
Sponsorship not specified$115k-$189kDetected 15 days ago
Machine LearningDeep LearningData AnalysisData ScienceNLPStatisticsCustomer SupportResearchLeadershipCommunicationProblem SolvingCritical ThinkingMentoringActuarial Science
About the role
- Join us to discover a culture that is rooted in innovation and thrives on collaboration.
- Imagine loving what you do and where you do it.
- Salary Range $114,700.00 - $189,200.00 Target Openings 12 What Is the Opportunity?
Responsibilities
- Demonstrated aptitude in identifying current or future problems or opportunities, analyzing data, synthesizing and comparing information to understand issues, identifying cause/effect relationships and exploring alternative solutions to support sound decision making.
- This three-year rotational program is designed to grow and develop your data science and self-leadership skills.
- You will work with business partners to develop an understanding of business needs and opportunities for data analysis and experiments.
- Leverage your expanding technical and business knowledge to build models that solve key business problems.
- Independently perform tasks to support the development of analytical solutions
- Develop domain and business knowledge to build statistical models.
- Perform other duties as assigned.
Requirements
- 1 year of related experience.
- Moderate working knowledge of modeling/research /analytics or actuarial required.
- Relevant statistical analysis work experience required.
- Knowledge of statistical techniques with the ability to read and revise statistical software programs.
- Ability to apply emerging statistical procedures to work.
- Ability to remain energized and focused in the face of ambiguity, change or strenuous demands.
- Proven customer service skills with the ability to provide service excellence to internal or external clients.
- Excellent communication skills with the ability to actively engage with others while maintaining a positive attitude.
- Ability to work together in situations when actions are interdependent, and a team is mutually responsible to produce a result.
- If you are a candidate and have specific questions regarding the physical requirements of this role, please send us an email so we may assist you.
Nice to have
- Heavy concentration in mathematics, including statistics and programming, business intelligence/analytics, as well as data science tools and research using large data sets.
- Additional verification of specific coursework will be required.
Compensation
- $114,700.00 - $189,200.00
- Travelers matches your 401(k) contributions dollar-for-dollar up to your first 5% of eligible pay, subject to an annual maximum.
- When you make a payment toward your student loan, Travelers will make an annual contribution into your 401(k) account.
Benefits
- Regression, Classification, Machine Vision, Natural Language Processing, Deep Learning and Statistical modeling.
- Employees and their eligible family members - including spouses, domestic partners, and children - are eligible for coverage from the first day of employment.
- You are also eligible for a Pension Plan that is 100% funded by Travelers.
- Start your career at Travelers with a minimum of 20 days Paid Time Off annually, plus nine paid company Holidays.
- The Travelers wellness program is comprised of tools, discounts and resources that empower you to achieve your wellness goals and caregiving needs.
- In addition, our mental health program provides access to free professional counseling services, health coaching and other resources to support your daily life needs.
- You will have the opportunity to explore multiple functions of analytics while learning from different leaders within Travelers.
- Travelers Data Scientists are taking the organization to the next level of intelligence by using advanced statistical techniques and machine learning algorithms.
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This listing is sourced directly from Travelers's careers page and normalized into a canonical job model.