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Insurance Information Technology & Data Scientist Curated Jobs List Dated August 23, 2018

Welcome to a Curated Job List compiled by Mid America Search. This List of Jobs, which our Client organizations are seeking to fill, have one or more factors of commonality thus Mid America Search has compiled or curated this collection of Jobs into the List below. Trustfully, our efforts will enhance your efficiency and provide time well spent in studying the information.

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Data Scientist (Two Jobs)
Job# 2779
Location:  Madison, WI
Education Requirements:  Bachelor’s Degree in Mathematics, Statistics, Physics, Computer Sciences or Engineering, or related field or equivalent experience. Preferred Candidates will have PhD in Computer Sciences or Engineering, Operations Research, Economics, Mathematics, or related field.
Other Requirements:  Include:

  • Specialized Knowledge and Skills Requirements:
  • Demonstrated experience providing customer-driven solutions, support or service.
  • Ability to work as part of a team and to communicate effectively.
  • Proficiency in programming languages suitable for database access, scripting, and statistical analysis. Familiarity with version control for software development.
  • Demonstrated experience using large amounts of structured, semi structured, and unstructured data.
  • Experience formulating, approaching, and solving problems on massive datasets.
  • Experience working with and analyzing massive sets of unstructured data.
  • Solid knowledge managing data to scale using data summarization, query and analysis software and tools.
  • Preferred Candidates will have the following:
  • P&C insurance fraud. Experience with fraud platforms such as SAS/FICO Fraud Framework, interactions with SIU and business teams in formulating business rules and incorporating them in models, additional feature engineering and link analytics, use of social media data for fraud, etc.
  • Experience with open source packages for:
    • Modeling (e.g. Torch, Tensorflow, scikit-learn, xgboost),
    • Visualization (e.g. matplotlib, ggplot, vega, d3.js) OR,
    • Data processing (e.g. Spark, Stanford CoreNLP, gensim).
  • Relational database and SQL skills.
  • Experience with cloud infrastructures.
  • Experience with tools and best practices for software engineering, including version control, testing, and review practices.

Salary Range:  $107k to $175k + 15% target bonus
Description:  Uses exploratory data analysis to provide innovative solutions to complex problems.  Works with business partners to understand what the business needs and issues are to address.  Applies knowledge of statistics, machine learning, programming, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to insights or improvements that have a significant financial impact on the organization.  Develops and evaluates predictive models and algorithms that lead to business solutions.  Generates and tests hypotheses and analyzes and interprets the results of experiments.  Communicates findings and recommendations to leadership and business partners.  Supports implementation efforts.  Job duties and responsibilities include:

  • Leverages machine learning and predictive modeling projects across a variety of problem domains or business initiatives, building predictive models to support business partner objectives and business needs.
  • Manipulates and investigates large and complex datasets and formulates data requirements and model specifications needed for development.  Incorporates findings and provides industry and competitor insights as part of model development and enhancement.
  • Works closely with business partners and domain experts to identify critical questions.
  • Working with domain experts, develops problem definition, analytical approach, and research design for modeling projects.
  • Works with business partners, both internal and external, to identify new opportunities and challenges.
  • Participates in the selection of research tools and technologies, design of a common research process, and brainstorming new opportunities and methodologies.
  • Researches and maintains awareness of industry best practices and business strategies.
  • Proactively brings in new and innovative ideas and approaches to develop business solutions.
  • Monitors industry and competitor trends to determine potential impact to predictive models.
  • Leverages emerging technologies, open source tools, and harnesses new mathematical techniques.

Data Scientist, Machine Learning (Three Jobs)
Job# 2778
Location:  Madison, WI
Education Requirements:  Bachelor’s, Master’s, or PhD degree in Mathematics, Statistics, Physics, Computer Sciences or Engineering , or related field; with an emphasis in machine learning, signal processing, computer vision and Data mining.
Other Requirements:  Include:

  • Top candidates will have 5+ years of NLP (Natural Language Processing) experience.
  • Experience in any of the following areas preferred:
    • Natural language processing to model customer interactions and insurance concept extraction
    • Image processing (Deep learning) for damage assessment.
    • Speech recognition.
    • Chatbots for customer service.
    • Recommendation engines for the insurance industry.
    • Applications of Deep learning.
  • Proficiency with the following tools preferred: Python, Spark, Tensorflow, CAFFE, familiarity with word embeddings, scikit-learn, Graph databases, Databases, AWS environments.
  • Specialized Knowledge and Skills Requirements:
    • Demonstrated experience providing customer-driven solutions, support or service.
    • Ability to work as part of a team and to communicate effectively.
    • Proficiency in programming languages suitable for database access, scripting, statistical analysis, and system development. Understanding of software development best practices including source control, coding standards and testing frameworks.
    • Demonstrated experience communicating complex findings in a clear and concise manner to divisional management.
    • Demonstrated experience developing and managing complex projects.
    • Demonstrated experience formulating, approaching, and solving complex analytical problems using a quantitative, scientific approach.
    • Demonstrated experience working with large, complex datasets using big data technologies and script.
    • Demonstrated knowledge and understanding of managing data to scale using data summarization, query, and analysis software and tools.

Salary Range:  $107k to $175k + 15% target bonus
Description:  The Data Scientist, Machine Learning job produces innovative solutions through the use of advanced data analytics from complex and high-dimensional datasets.  Works with business partners to understand what the business needs and issues are to address.  Applies knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries to meet a variety of business challenges.  Develops and evaluates predictive models and advanced algorithms that lead to business solutions.  Conducts the complex and vital analytics work critical to the organization.  Assists with complex projects that yield actionable insights used by senior management to make strategic, data-driven business decisions.  Communicates findings and recommendations to leadership and business partners.  Participates in implementation efforts.  Depending on qualifications, candidates may be hired at the Data Scientist I or II level.  Job duties and responsibilities include:

  • Creates business application and modeling framework, for new datasets, and discovers insights and relationships from large/complex datasets through investigative research using advanced mathematical and/or statistical techniques.
  • Explores data using a variety of advanced statistical techniques to proactively identify relationships, create insights and answer business questions or guide future model development.
  • Build the hypothesis, identify research data attributes and determine best approach to address business issues.
  • Combines business acumen with mathematical capabilities to build complex predictive models to support business objectives.
  • Builds complex programs for running mathematical or statistical tests on data and for understanding complex relationships across attributes.
  • Incorporates findings and provides industry and competitor insights as part of model development and enhancement.
  • Researches and maintains awareness of industry best practices and business strategies.
  • Brings new and innovative ideas and approaches to develop business solutions.
  • Monitors industry and competitor trends to determine potential impact to predictive models.
  • Incorporates findings and provides industry and competitor insights as part of model development and enhancement.
  • Identifies, leverages and develops expertise in emerging technologies, open source tools, and harnesses new techniques (e.g., machine learning).
  • Networks with and contributes thought leadership to the broader external analytics community.  Builds awareness of leading techniques, tools, and data resources.
  • Assists with complex research or analytics projects related to large, complex business initiatives.
  • Interacts with company senior leadership to inform on industry trends and emerging research topics.  Serves as internal expert for new areas of analytics exploration.

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