At the heart of what we do is help clients manage risk. Verisk (Nasdaq: VRSK) provides data and insights to our customers in insurance, energy and the financial services markets so they can make faster and more informed decisions.
Our global team uses AI, machine learning, automation, and other emerging technologies to collect and analyze billions of records. We provide advanced decision-support to prevent credit, lending, and cyber risks. In addition, we monitor and advise companies on complex global matters such as climate change, catastrophes, and geopolitical issues.
But why we do our work is what sets us apart. It stems from a commitment to making the world better, safer and stronger.
It’s the reason Verisk is part of the UN Global Compact sustainability initiative. It’s why we made a commitment to balancing 100 percent of our carbon emissions. It’s the aim of our “returnship” program for experienced professionals rejoining the workforce after time away. And, it’s what drives our annual Innovation Day, where we identify our next first-to-market innovations to solve our customers’ problems.
At its core, Verisk uses data to minimize risk and maximize value. But far bigger, is why we do what we do.
At Verisk you can build an exciting career with meaningful work; create positive and lasting impact on business; and find the support, coaching, and training you need to advance your career. We have received the Great Place to Work® Certification for the fifth consecutive year. We’ve been recognized by Forbes as a World’s Best Employer and a Best Employer for Women, testaments to our culture of engagement and the value we place on an inclusive and diverse workforce. Verisk’s Statement on Racial Equity and Diversity supports our commitment to these values and affecting positive and lasting change in the communities where we live and work.
Job Description
Verisk Insurance Solutions is looking for a Senior Data Scientist to join the Claims team.
- Serve as the technical resource in the conception and development of new predictive modeling initiatives, with some supervision
- Suggest and develop innovative analytic methods that result in a technically superior product and/or create a competitive advantage, as well as meet design requirements and project timeline
- Research, evaluate, and recommend internal and external data sources and coordinate with data resources
- Serve as the senior technical person on data cleansing, variable creation, variable transformation, etc., as well as best-practices in the creation of analytic datasets
- Serve as the consummate technical person in model development and validation analyses - from driving pragmatic practice of methods to devising novel solutions and diagnostic measures, to coaching and mentoring junior staff
- Act as senior technical person in development and execution of methods to address needed business diagnostics; review, and aid productization and deployment
- Provide significant input to Product Management on implementation specifications and production testing
- Act as senior technical person to develop process and metrics to monitor model performance
- Review reports and make recommendations for needed model refits / enhancements
- Keep abreast of business trends / product needs
- Research literature to stay current on technical methods to solve specific problems
Qualifications
- Graduate degree (M.S. required, Ph.D. preferred) in a quantitative discipline
- 2+ years professional experience building predictive and descriptive models
- Exposure to the property & casualty industry is desirable, and experience with medical, clinical, fraud & abuse and pharmacy data analytics is a big plus
- Experience, and expertise in diverse statistical and data mining techniques (e.g. - GLM/Regression, Boosting, Random Forest, Trees, Clustering, PCA, SVM, text mining, social network analysis etc.)
- Demonstrated proficiency with statistical packages in Spark ML-Lib, Python, R, or SAS is a must
- Ability to program in Python, Spark, Scala, R, or SAS is highly desirable
- Understanding of RDBMs and interactive SQL programming skills are a must
- Experience with Big Data technologies like Hadoop, Spark, Hive, NoSQL, etc., and Cloud technologies (AWS, Azure, etc.) is highly desirable
- Aptitude for picking up new technologies is expected
