Data Scientist

Employer
Connecticut State Jobs
Location
Hartford, CT
Closing date
Oct 20, 2021

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Sector
Science, Mathematics and Statistics
The Position:

The CID is currently recruiting for a Data Scientist position for the Department of Insurance. We are looking for someone knowledgeable in Statistical Analysis System (SAS), Revolutionary R, or other computer programming software systems. We are located at 153 Market Street in Downtown Hartford, easily accessible for all commuters. This position is full-time, 40 hours a week, Monday-Friday.

In this role you will be responsible for:

Data Science Program - Continue developing the processes to use the databases/reports at CID to monitor the financial solvency of the insurance companies and the marketing conducts in availability and affordability, complaints, etc.
Climate Risk Reporting - Develop the program to monitor the climate risk related activities.
Cyber Risk - Develop a monitoring measurement as an early indicators to prevent financial failure of the cyber risk insurance markets in CT.
AI, ML and Predictive Modeling projects - Assist in developing the program to validate the data usage, modeling risks, etc.
We participate in a competitive benefits plan that includes healthcare coverage, a retirement plan, as well as, paid time off!

Selection Plan

All State employees shall follow the guidelines as listed in Executive Orders 13F (3a) and 13G (3a) .

The minimum experience and training requirements must be met by the close date on the job opening, unless otherwise specified.

Note: At any point during the recruitment process, applicants may be required to submit additional documentation which support their qualification(s) for this position. These documents may include: a cover letter, resume, performance reviews, attendance records, supervisory references, licensure, etc., at the discretion of the hiring agency. Applicants must meet the minimum qualifications as indicated to apply for this position.

The immediate vacancy is listed above, however, applications to this recruitment may be used for future vacancies in this job class.

This posting may require completion of additional referral questions (RQs). You can access these RQs via an email that will be sent to you after the postings closing date or by visiting your JobAps Personal Status Board (Certification Questionnaires section). Your responses to these RQs must be submitted by the questions expiration date. Please regularly check your email and JobAps Personal Status Board for notifications. Please check your SPAM and/or Junk folders on a daily basis in the event an email provider places auto-notification emails in a users spam.

Should you have questions pertaining to this recruitment, please contact Jennifer Neumann at jennifer.neumann@ct.gov and reference the recruitment number.

Purpose Of Job Class (Nature Of Work)

In a state agency this class is accountable for directing and conducting the most complex and specialized research investigations/evaluations, statistical analysis and/or data driven studies/projects.

Examples Of Duties

Applies statistical and research principles and techniques to a wide variety of issues and projects; develops research designs and statistically sound protocols and works with staff to carry out specific research studies; develops statistical and computerized models for analyzing data and interprets results to support business and client needs and facilitate informed recommendations and decisions; performs complex statistical analyses such as predictive modeling, forecasting, multiple regression, trend analysis, log linear analysis, factor analysis, and multi-variate analysis; uses parametric and non-parametric statistics; selects, designs, organizes and works out statistical techniques and research designs most suitable for the project/study at hand; evaluates the strengths and weaknesses of various statistical techniques and research designs, selecting those which achieve the most valid results; conducts in-depth literature searches and writes scientific papers; instructs staff in research and statistical techniques, methods, and use of statistical analysis software; oversees the production of research proposals, development and maintenance of databases, and interpretation, and writing of research and statistical reports for various intra and extra departmental audiences; may assist in the planning, design, selection, and evaluation of technologies related to data retrieval and analysis; performs related duties as required.

Knowledge, Skill And Ability

Considerable knowledge of methods of research design, statistical analysis and database management; considerable knowledge of management systems research and development related to social and economic trends; considerable knowledge of relevant State and Federal statutes, regulations and guidelines; knowledge of data processing computer programming for statistical analysis; knowledge of data retrieval and analysis methods; considerable written and oral communication skills; considerable interpersonal skills; ability to conduct longitudinal investigations/research, including interviewing and performing trend analyses and outcome effectiveness studies; ability to analyze and evaluate data using multiple regression, log linear analyses, factor analyses and multi-variate analyses; ability to use statistical packages and/or various data modeling platforms; ability to design and conduct studies and determine effective solutions; ability to write technical reports; some supervisory ability.

Minimum Qualifications - General Experience

A Master's degree in biostatistics, epidemiology, public health, psychology, statistics or a closely related area with significant coursework in research methodology and statistics and one (1) year of professional experience with significant involvement in research and statistical analysis.

Preferred Qualifications

The successful candidate will possess:

Experience presenting regulatory positions and determinations to insurance company representatives.
Experience applying statistical research and techniques to projects.
Experience of machine learning techniques: clustering, regression, classification, graphical models, and mixture models.
Ph.D. in statistics, mathematics, or data science.

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