Senior Data Scientist III

Do you love collaborating with teams to solve complex problems and deliver solutions?

Would you like to partner with the biggest names in the insurance industry?

About the Business

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Insurance vertical, we provide customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. Our insurance risk solutions help drive better data-driven decisions across the insurance policy lifecycle – all while reducing risk. You can learn more about LexisNexis Risk at the link below. https://risk.lexisnexis.com/insurance

About our Team

The Insurance Analytics team is dedicated to harnessing the power of data and sophisticated analysis to assess risks and enhance decision making for insurance carriers. At LexisNexis Risk Solutions, we pride ourselves on employing advanced statistical models and predictive algorithms to provide valuable insights that enable insurance providers to make informed decisions.

About the role

We are looking for a Sr. Data Scientist to join the Insurance Analytics team with strong expertise in statistics/modeling, machine learning to join our diverse team of data scientists. You will play a key role in new product innovation, model development, generating actionable insights along with working closely with the Vertical and Product teams to design and implement new solutions that are cutting edge supporting the insurance market. A Senior Data Scientist III should be able to define scope of a project and execute that project independently. Individuals in this role are expected to support the development and training of junior staff. They develop best practices and are the project leaders. Ideally, the candidate will have actuarial education or experience.

You will be responsible for:

• Researching and developing new statistical/machine learning models to analyze structured and unstructured data by ideating and experimenting with new methodologies to generate predictive scores and attributes.

• Exploring and mining new data sources to help optimize and validate existing models.

• Leading the design and development of data driven solutions and the development of machine learning/statistical models to build risk segmenting and predictive models.

• Ideating, researching, and designing new and innovative analytics and data science methodologies on large scale and complex data assets.

• Having a thorough understanding of the team's core functions and technologies.

• Working with peers to share subject matter expertise, transfer skills, and develop knowledge base.

• Developing and utilizing innovative strategies to complete business analysis and evaluate the performance of business segments.

• Reviewing data results and communicating findings to stakeholders.

• Enforcing data quality testing best practices. Performing all other duties as assigned.

  Qualifications:

• Have graduate degree (Masters or PhD) in Statistics, Actuarial Science, Data Science, Engineering, Computer Science, or a Quantitative field. Actuarial experience or designation is a plus.

• Have experience in statistical modeling and preferably related to credit or insurance industry.

• Have 5+ yrs. of hands-on statistical model development/machine learning (ML) experience, preferably with at least 2 years’ experience related to credit or insurance industry.

• Have solid understanding of ML techniques and statistical methods including hypothesis testing, sample design, model development (linear and non-linear models), validation of machine learning models.

• Have expert programming skills in Python and/or R, with extensive experience with their standard data manipulation and ML packages: pandas, scikit-learn, NumPy, XGBoost, Pyspark in Python and rpart, party, caret in R).

• Have proven ability as a self-starter to learn new technologies (Pyspark, ECL, Azure/AWS ML Services), programming languages, and to share cross-functional knowledge across the teams.

• Have solid verbal and written communications skills and be comfortable presenting analytical results to senior leadership and business stakeholders.

• Have experience in data management and data analysis in on-premise and cloud database management systems (like SQL Server, Cosmos DB, Blob storage, etc.)

• Have excellent attention to detail, organization, and documentation.

  Learn more about the LexisNexis Risk team and how we work here (https://relx.wd3.myworkdayjobs.com/RiskSolutions/page/21c296c982531000b79663f3194b0000)

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At LexisNexis Risk Solutions, having diverse employees with different perspectives is key to creating innovative new products for our global customers. We have 30 diversity employee networks globally and prioritize inclusive leadership and equitable processes as part of our culture. Our aim is for every employee to be the best version of themselves. We would actively welcome applications from candidates of diverse backgrounds and underrepresented groups.

We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form: https://forms.office.com/r/eVgFxjLmAK , or please contact 1-855-833-5120.

Please read our Candidate Privacy Policy (https://www.relx.com/careers/join-us/privacy) .

RELX is a global provider of information and analytics for professional and business customers across industries.

We help scientists make new discoveries, lawyers win cases, doctors save lives and insurance companies offer customers lower prices. We save taxpayers and consumers money by preventing fraud and help executives forge commercial relationships with their clients.

In short, we enable our customers to make better decisions, get better results and be more productive.