Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch
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
· Under supervision, executes project plans for timely project completion.
· Provides technical advice to junior team members
· Utilizes statistical and machine learning techniques to create high-performing
models that comply with regulatory and privacy requirements and address business
objectives and client needs.
· Performs analyses of structured and unstructured data to solve multiple and
complex business problems. utilizing advanced statistical, mathematical and
machine learning technique.
· Ability to research and develop new approaches, keeping up to date.
Tests new statistical analysis methods, software and data sources for continual
improvement of quantitative solutions. Implements as needed.
· Creates clear and easy to understand documents for product support (technical).
· Presents analysis ideas, progress reports and results to internal managers, project
managers.
· Collaborates with Lead Data Scientist to develop technical/business approaches
and new or enhanced technical tools. Participates in collaborations for
implementation.
· Completes all responsibilities as outlined on annual Performance Plan.
· Completes all special projects and other duties as assigned.
· Must be able to perform duties with or without reasonable accommodation.
Qualifications
· Graduate-level degree preferred with concentration in a quantitative discipline such as statistics,
mathematics, economics, operations research, computer science or aligned discipline.
· Skilled with feature engineering and selection methodologies.
· Knowledge in and applied experience with statistical and machine learning.
· Experience (2-4 years) using statistical and machine learning computer languages (e.g. R, Python, SLQ).
· Working familiarity with cloud computing environments.
· Logical, evidence-based problem solving and critical thinking skills.
· Team focused and evidence of supporting project team members.
Preferred:
· Exposure to image classification or recognition.
· Experience with deep learning and/or text analytics.
· Insurance experience, focusing on personal lines or related business content.
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Verisk is a leading data analytics provider serving customers in insurance, energy and specialized markets, and financial services. Our team of nearly 9,000 helps customers make crucial decisions every day about risk—with greater precision, efficiency, and discipline.