Data Scientist

Berkshire Hathaway Homestate Companies

9d•$116,570 - $149,330•Hybrid

About The Position

Berkshire Hathaway Homestate Companies, Workers Compensation Division, has an opening for a Data Scientist to join the Analytics team. This position is responsible for developing supervised and unsupervised models, conducting advanced analysis, or otherwise utilize data which improve the operations of the company. This individual will focus on repeatable processes and solutions that predict, identify, or analyze business trends through complex data analysis or modeling, continually interpreting results from multiple sources using a variety of techniques, ranging from simple data aggregation via statistical analysis to moderately complex data mining and machine learning techniques applied to structured and unstructured data while working collaboratively with senior level staff.

Requirements

EDUCATION: Bachelor's degree in Computer Science, Statistics, or related field from an accredited four-year college or university.
EXPERIENCE: Minimum of 2 years of experience in Data Science creating and optimizing models using latest tools such as R, Python, Spark, Hadoop, SAS, etc. required.
TECHNICAL KNOWLEDGE: Knowledge and understanding of analytical tools, such as SAS, Excel, SQL, R, Python, Spark, etc.
MATH AND REASONING ABILITY: Able to solve practical problems and deal with a variety of variables in situations where only limited standardization exists. Able to interpret a variety of instructions furnished in written, oral, diagram, or schedule form. Ability to apply advanced mathematical concepts such as exponents, logarithms, quadratic equations, and permutations. Ability to apply mathematical operations to such tasks as frequency distribution, determination of test reliability and validity, analysis of variance, correlation techniques, sampling theory, and factor analysis.
LANGUAGE ABILITY: Ability to read, analyze, and interpret general business periodicals, professional journals, technical procedures, and data from various sources. Ability to develop briefings and reports and effectively communicate complex concepts and findings to both technical and nontechnical stakeholders both in individual conversations and presentations to groups. Ability to write effective business correspondence and clear, concise procedures. Makes persuasive arguments.

Nice To Haves

Experience with cloud native machine/learning/AI tools such as DataBricks, SageMaker, etc. preferred.
Insurance industry background, especially workers compensation, is highly desirable.

Responsibilities

Develops and deploys machine learning models using the latest techniques using software like python, R or similar.
Researches the latest analytical techniques for modeling structured and unstructured data.
Follows modern source control of all model code utilizing source control software such as Git or ADO repositories.
Combines, manipulates, and transforms large, complex datasets using Python and SQL to identify patterns, anomalies, and trends within the data so that it can be prepared for use in machine learning models, business intelligence reporting, machine learning operations, and prepare it for any end user as meaningful information.
Prepares and presents data in dashboards, reports or other formats which include charts, graphs, tables, other visualizations, or analytical output to convey the results of data analysis using python, SQL, power BI, or other appropriate statistical or data science software.
Applies machine learning models which perform optical character recognition on unstructured data to prepare it for downstream analytics such as search, word vectorization, sentence encoding and other data science based unstructured modeling approaches.
Proposes and evaluates innovative solutions for analyzing, clustering, associating, and classifying data.
Develops and validates algorithms via analysis, computer simulation, and prototyping.
Helps maintain large-scale analytics infrastructure, including distributed storage and computation clusters. Hands-on development and programming.
Develops and deploys systems and programs for machine learning operations tasks which monitor and rebuild machine learning and other similar models and systems.
Detects anomalies on features and model predictions using advanced statistical modeling and process control statistical techniques.