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Data Scientist

Warren, NJ 07059

Posted: 08/10/2023 Category: Data Science Job Number: 283111-1_1 Salary: $140,000 - 160,000

Job Description

Title: Data Scientist
Location: Warren, NJ
Salary: $140,000 - 160,000
Contact: Paul Chatlos, [email protected]

Data Scientist Position Overview:

We are seeking a highly experienced Data Scientist with domain knowledge of one industry (Property & Casualty Insurance or OEM are welcome) and analytical expertise as described below. The successful candidate will participate in advanced analytics initiatives, and provide critical insights to inform strategic decision-making to the management team and our group companies.
Data Scientist Essential Functions:
-Our main KPIs are (i) growing the direct written premium, (ii) improving the loss ratio in terms of price adequacy, UW accuracy, etc, (iii) exploring new business opportunities as a Data-driven insurer. You will have access to a wide variety of data across multiple organizations and be expected to deliver results in the following analytical tasks.
-Modeling: Develop, test, validate, and implement statistical/predictive models using cutting-edge algorithms and diverse data sources.
-Analytics: Use analytical applications and languages, such as Python and tools in Azure, to identify trends and relationships among disparate data, draw appropriate conclusions, and translate analytical findings into business strategies or analytics software.
-Data Engineering: Build ETL processes to source and link data in preparation for model/algorithm development. Be an expert on the data sets in the environment, third-party data assessments, and data quality.

Data Scientist Qualifications:

-Master's degree in a quantitative field (e.g. computer science, applied mathematics, business analytics, physics, operations research, statistics, artificial intelligence or engineering)
-2+ years of experience working as a data scientist in the insurance business, or domain knowledge in at least one other industry.
-Strong written, verbal, and interpersonal communication skills. Ability to communicate effectively at all levels in the organization.
-Experience in the following disciplines: scripting languages (e.g. Python), SQL, and big data tools and/or cloud environments (e.g. AWS,GCP or Azure)
-Experience in statistical and machine learning techniques such as linear regression, logistic regression, survival analysis, GLM, classification, feature engineering, dimensionality reduction, model validation.
-Strong understanding of domain knowledge in at least one industry, such as automated underwriting models using Al, claims processing, reserve analysis, fraud detection, weather forecast/climate change, mobility platform or autonomous driving technology, for example. In the interview, we will ask you to present your analytical accomplishments in your previous position.
-Strong knowledge in Machine Vision, Natural Language Processing, Deep Learning. Requirements include standard data science libraries and frameworks such as scikit-learn, Tensorflow/PyTorch. PySpark, etc.
-Familiarity with automotive OEM connected vehicle data and related infrastructures (ADAS, LiDAR, etc.).

Meet Your Recruiter

Paul Chatlos

Paul Chatlos joined Smith Hanley in 2013. He is currently the Data Science and Analytics Practice Lead for the East and West Coasts and a Principal of the company. Prior to joining Smith Hanley, he recruited marketing professionals in the pharmaceutical, medical device and biotechnology industries and also worked in Physician Recruitment. He prides himself on building excellent relationships with both clients and candidates in order to best address their hiring needs and career goals. He also believes that recruiting is finding the best “match” of candidate and opportunity. 

He holds a BS in Psychology from James Madison University. Outside of work, Paul enjoys playing golf regularly and is an avid sports fan. 

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