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Assistant Director, Data Science - job 1 of 3

Pay Philosophy

The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role.

Description

The creative problem solvers in Liberty Mutual’s Insights & Solutions group harness the power of data, analytics and technology to develop innovative solutions that drive our US Retail Markets business forward and support a high-performing culture. This group brings together highly talented thinkers and doers ready to challenge the status quo and make an impact. As a member of this cross-functional group, you’ll collaborate with teams across Liberty Mutual to deliver analysis that unlocks insights and sparks new, better ways of working.

 

The US Retail Markets Data Science team brings together a diverse range of talent to predict future risk and what our customers will need to recover. Our data engineers write code that turns trillions of bits of information into structured data—data that our hundred-plus Data Scientists analyze with cutting-edge modeling techniques to unlock insights. From there, our tools and deployment teams ensure this data can be practically applied to business pr

 

Join the Property & Specialty Product Design & Modeling department to develop industry-leading pricing and underwriting models. We pride ourselves in developing the best-in-class models and making the team an awesome place to work! The P&S PDM team turns DS insights into business value and partners closely with business stakeholders to expertly align risk with rate.

 

Analyst roles within the team range from leaning more heavily into research to inform our product design, to directly interfacing with regulators and Profit & Loss owners. Our analysts make an impact by improving model fits, researching new modeling techniques, increasing the speed of model deployments, improving capabilities to test, calibrate, and monitor models, and serving as technical experts to explain our models to the broader Property & Specialty organization. With opportunities for growth, mentorship, and engagement with the data science community, we offer a stimulating environment for those with a passion for technical excellence and problem-solving.

 

The Property & Specialty Product Design and Modeling team is hiring an individual contributor to work on predictive modeling for our core UW programs. The ideal candidate is proactive and intellectually curious, resilient, highly technical, and can efficiently think through complex business questions independently. The person in this role will report to Jonathan Woelfel and also have opportunities to collaborate directly with teams in US Data Science, including Data Science Excellence and Infrastructure.

 

Level of position offered will be based on skills and experience at manager discretion.**

 

**This role may have in-office requirements based on candidate location.*

 

Job responsibilities:

  • Mine large datasets using sophisticated analytical techniques to generate insights and inform business decisions
  • Independently build and interpret complex UW models for Property & Specialty, incorporating learnings from other lines of business as appropriate
  • Explore and utilize advanced modeling techniques and strategies to improve model sophistication
  • Collaborate with Underwriting Effectiveness, State Management, IT, and other business partners to help implement new UW models
  • Enable the business to make clear tradeoffs among choices, with a reasonable view into likely outcomes.
  • Understand the competitive marketplace, business issues, and data challenges to deliver actionable insights, recommendations and business processes
  • Effectively communicate results in written, oral, and presentation formats
  • Act as a mentor and help develop less experienced analysts on the team
  • Regularly engage with the data science community and lead cross functional working groups.
  • Drive innovation in the application and development of tools and practices.

Qualifications

  • Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
  • Expert knowledge of predictive toolset; reflects as expert resource for tool development.
  • Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
  • Networks with key contacts outside own area of expertise. Ability to establish and build relationships within the aligned functional area or SBU.
  • Ability to give effective training and presentations to peers, management and less senior business leaders.
  • Ability to use results of analysis to persuade team or department management to a particular course of action.
  • Has a value driven perspective with regard to understanding of work context and impact.
  • Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 2 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of 4 years of relevant experience or may be acquired through a Bachelor`s degree(scientific field of study) and a minimum of 5+ years of relevant experience.

About Us

As a purpose-driven organization, Liberty Mutual is committed to fostering an environment where employees from all backgrounds can build long and meaningful careers. Through strong relationships, comprehensive benefits and continuous learning opportunities, we seek to create an environment where employees can succeed, both professionally and personally.At Liberty Mutual, we believe progress happens when people feel secure. By providing protection for the unexpected and delivering it with care, we help people embrace today and confidently pursue tomorrow.We are proud to support a diverse, equitable and inclusive workplace, where all employees feel a sense of community, belonging and can do their best work. Our seven Employee Resource Groups (ERGs) offer a centralized, open space to bring employees and allies together to connect, learn and engage.We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://LMI.co/BenefitsLiberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.Fair Chance Notices

  • California
  • Los Angeles Incorporated
  • Los Angeles Unincorporated
  • Philadelphia
  • San Francisco

Average salary estimate

$100000 / YEARLY (est.)
min
max
$80000K
$120000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Assistant Director, Data Science, UNAVAILABLE

As an Assistant Director of Data Science at Liberty Mutual, you're stepping into an empowering role where your analytical prowess will shine. You'll be part of the Insights & Solutions group, working alongside a talented team of diverse thinkers who are dedicated to redefining data usage in the US Retail Markets sector. Your creativity and expertise will be key in mining extensive datasets and developing robust underwriting models that align risk with reward. You'll get to collaborate with various stakeholders, dive into complex modeling techniques, and mentor up-and-coming analysts. At Liberty Mutual, we're not just about the numbers; we foster a vibrant culture that encourages continuous learning and innovation. If you're proactive, technically skilled, and passionate about translating data insights into business value, this remote position will provide you with the opportunity to make a substantial impact. Join us as we harness the latest in data analytics to enhance the customer experience and drive our business forward. Your role will be pivotal in shaping our industry-leading pricing models while collaborating closely with teams across the company. The atmosphere is supportive and growth-oriented, with a firm commitment to diversity and inclusivity. Experience the benefits of working with a knowledgeable team while utilizing state-of-the-art modeling techniques to lead the charge in predictive analytics. Welcome to your next adventure with Liberty Mutual!

Frequently Asked Questions (FAQs) for Assistant Director, Data Science Role at UNAVAILABLE
What are the main responsibilities of the Assistant Director, Data Science at Liberty Mutual?

The Assistant Director, Data Science at Liberty Mutual is responsible for mining large datasets using advanced analytical techniques, developing and interpreting underwriting models, and collaborating with various business partners. This role requires effective communication and mentorship to guide less experienced analysts, while driving innovation in model development and application.

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What qualifications are required for the Assistant Director, Data Science position at Liberty Mutual?

Candidates for the Assistant Director, Data Science role at Liberty Mutual typically need to possess at least a Master’s degree in a scientific field and a minimum of four years of relevant experience or a Bachelor's degree with five years of experience. A Ph.D. is preferred, along with a broad knowledge of predictive analytic techniques and strong communication skills.

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What skills are essential for success as an Assistant Director, Data Science at Liberty Mutual?

Essential skills for the Assistant Director, Data Science role at Liberty Mutual include a deep understanding of predictive analytic techniques, the ability to communicate complex ideas clearly, and expertise in the predictive toolset. The ideal candidate should also have strong mentoring capabilities and the capacity to engage effectively within a cross-functional team.

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How does the Assistant Director, Data Science at Liberty Mutual contribute to the company's success?

The Assistant Director, Data Science at Liberty Mutual contributes significantly by developing innovative pricing and underwriting models that enhance decision-making and align risk with reward. By turning data insights into actionable strategies, this role helps to drive business growth and improve overall performance in the competitive insurance marketplace.

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Is remote work available for the Assistant Director, Data Science position at Liberty Mutual?

Yes, the Assistant Director, Data Science role at Liberty Mutual offers the flexibility of remote work, although there may be specific in-office requirements depending on the candidate’s location. This allows for a balanced work environment conducive to productivity and innovation.

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Common Interview Questions for Assistant Director, Data Science
Can you describe your experience with predictive modeling techniques in relation to the Assistant Director, Data Science role?

It’s essential to provide detailed examples of your work with predictive modeling techniques, including specific tools and methodologies you've employed. Be ready to discuss any challenges you faced and how you overcame them, along with the outcomes of your models.

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How do you approach data analysis when faced with large and complex datasets?

Discuss your systematic approach to data analysis, including your steps for cleaning, processing, and deriving insights from complex datasets. Highlight any tools or software you utilize and any specific projects that demonstrate your ability to draw valuable conclusions from extensive data.

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How would you communicate complex findings to stakeholders who may not have a technical background?

Explain your strategy for simplifying complex data insights into clear, actionable recommendations. Provide examples of how you've successfully communicated your findings in previous roles, perhaps through visualizations or simplified reporting.

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What role does mentorship play in your work style as an Assistant Director, Data Science?

Highlight your belief in the importance of mentorship and how you've previously supported junior analysts or team members. Provide examples of mentoring approaches you've taken and the positive impact it has had on team dynamics and growth.

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Can you provide an example of a successful project you've led that involved cross-functional collaboration?

Share a specific project that illustrates your ability to work with diverse teams. Describe your role in facilitating collaboration, the outcomes achieved, and any feedback received from team members after the project's completion.

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What tools do you consider essential for performing your duties as an Assistant Director, Data Science?

Discuss the various analytical and modeling tools you are proficient in, such as Python, R, or specific statistical software. Elaborate on how these tools have enabled you to derive insights and develop models effectively.

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How do you stay updated on advancements in data science and analytics?

Share your commitment to continuous learning through attending workshops, enrolling in online courses, or participating in data science communities. Discuss any specific resources or forums that you rely on to keep your knowledge current.

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What challenges have you faced in your previous data science roles, and how did you overcome them?

Describe specific challenges related to data modeling or analytics you've encountered and the strategies you implemented to address them. Focus on problem-solving and the lessons learned to demonstrate resilience and innovation.

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In your opinion, what is the most important aspect of developing successful predictive models?

Share your perspective on model accuracy, interpretability, and alignment with business objectives. Emphasize the balance between technical sophistication and practical application, showcasing relevant experiences to back your argument.

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How do you ensure your predictive models remain relevant in a rapidly changing environment?

Talk about techniques you employ to periodically review and refine your models as conditions shift. Discuss the importance of collaboration with stakeholders to identify changing data needs and the steps you take to adapt your models accordingly.

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EMPLOYMENT TYPE
Full-time, remote
DATE POSTED
April 20, 2025

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