Data Science Team Lead at Verisk

Company Description

At Verisk, we help the world see new possibilities and inspire change for better tomorrows. Our analytic solutions bridge content, data, and analytics to help businesses, people, and society become stronger, more resilient, and sustainable.

Job Description

Verisk is seeking an experienced Data Scientist to join our team as a Data Science Team Lead. This role involves supporting the development of various analytics models and supervising junior data scientists. The ideal candidate will have extensive data science experience, proficiency in Python, and the ability to develop models using GLMs and machine learning techniques. This is an exciting opportunity offering career growth and development.

Role Responsibilities

• Support the Analytics Team in building new analytics products for claims and underwriting.
• Execute data analysis and exploratory analysis, including project design, data processing, cleaning, merging disparate data sources, feature engineering, performing analyses, and communicating results.
• Produce models using a variety of algorithms (GLM, GBM, Random Forest, Neural Networks, etc.) and assess their relative strengths.
• Identify relevant and predictive factors to include in model builds.
• Document processes, code, implement version control, and create functions/template code for application to new data with minimal effort.
• Create clear, understandable reports and verbally present analysis ideas, progress, and results to colleagues.
• Support a high-performance, collaborative culture and participate in peer-review to produce high-quality results.

Qualifications

• Masters/PhD in Mathematics, Science, or an Analytics-related discipline.
• Solid programming experience with Python and SQL.
• Experience with data manipulation, validation, modeling, or statistical techniques.
• Excellent written and verbal communication skills.
• Detail-oriented technical aptitude with strong problem-solving and decision-making skills.
• Fluency in English.

We Offer

• Professional development and growth opportunities.
• Leadership experience opportunities.
• A collaborative and inclusive work environment.
• Flexible working hours and a hybrid work model.
• Performance-related bonus.
• Private life insurance, health care, and a Multisport card.

About Verisk

For over 50 years, Verisk has been the leading data analytics and technology partner to the global insurance industry. We deliver value to our clients through expertise and scale, empowering communities and businesses to make risk decisions faster.

At Verisk, you'll have the chance to use your voice and build a rewarding career that's as unique as you are, with work flexibility, support, coaching, and training to succeed. For the eighth consecutive year, Verisk is proudly recognized as a Great Place to Work® for outstanding workplace culture in the US, UK, Spain, India, and Poland. We value learning, caring, and results, and inclusivity and diversity are top priorities.

We’re 7,000 people strong, relentlessly pursuing innovation. Join us and help translate big data into big ideas, creating a better future for everyone.

Verisk Businesses

• Underwriting Solutions: Providing underwriting and rating solutions for better risk assessment.
• Claims Solutions: Supporting end-to-end claims handling with analytic and automation tools.
• Property Estimating Solutions: Offering property estimation software for efficient workflows.
• Extreme Event Solutions: Providing risk modeling solutions for resilience to extreme events.
• Specialty Business Solutions: Offering integrated software for end-to-end insurance and reinsurance management.
• Marketing Solutions: Delivering data and insights for consumer engagement.
• Life Insurance Solutions: Offering end-to-end capabilities for carriers, distribution, and customers across the policy lifecycle.
• Verisk Maplecroft: Providing intelligence on sustainability, resilience, and ESG.

Verisk Analytics is an equal opportunity employer. We consider all qualified applicants without regard to race, religion, color, national