Data Scientist

ESSENTIAL 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.

QUALIFICATIONS

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

DESIRED COMPETENCIES

• Analytical Thinking
• Innovation and Initiative
• Results Orientation
• Effective Communication and Collaboration

WHAT WE OFFER

• Hybrid Work Schedule (up to 2 days work from home upon eligibility)
• Multiple Office Locations - Financial District Downtown or Walnut Creek
• Paid Time Off
• Paid Holidays
• Immediate Vesting of Retirement Savings + Company Match
• Group Health Insurance (Medical, Dental, and Vision)
• Life and AD&D Insurance
• Long Term Disability Insurance
• Hospital Indemnity Insurance
• Accident and Critical Illness Insurance
• Flexible Savings Accounts
• Paid Community Volunteer Day
• Employee Assistance Program
• Tuition Reimbursement Program
• Employee Referral Program
• Diversity, Equity and Inclusion Program