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Senior Data Scientist

Job in Bakersfield, Kern County, California, 92189, USA
Listing for: Mitchell International
Full Time position
Listed on 2026-10-30
Job specializations:
  • IT/Tech
    Data Scientist, Data Engineering, Machine Learning/ ML Engineer, Data Analyst
Salary/Wage Range or Industry Benchmark: 110000 - 135000 USD Yearly USD 110000.00 135000.00 YEAR
Job Description & How to Apply Below
Mitchell International Senior Data Scientist

US–Remote

Job
-19519

Type:
Regular Full-Time

# of Openings: 1

Category:
Product & Program Management

Mitchell International, Inc.

Overview

At Enlyte, we combine innovative technology, clinical expertise, and human compassion to help people recover after workplace injuries or auto accidents. We support their journey back to health and wellness through our industry-leading solutions and services. Whether you're supporting a Fortune 500 client or a local business, developing cutting-edge technology, or providing clinical services you'll work alongside dedicated professionals who share your commitment to excellence and make a meaningful impact.

Join us in fueling our mission to protect dreams and restore lives, while building your career in an environment that values collaboration, innovation, and personal growth.

Be part of a team that makes a real difference.

Responsibilities

Key Responsibilities

  • Design, develop, and implement machine learning models and algorithms to address business problems related to medical claims
  • Conduct exploratory data analysis to identify patterns, trends, and insights
  • Clean, preprocess, and transform large, complex datasets to ensure data quality
  • Create compelling data visualizations and dashboards to communicate findings to technical and non-technical stakeholders
  • Collaborate with engineering teams to deploy models into production environments
  • Monitor model performance and implement improvements as needed
  • Mentor junior data scientists and contribute to best practices documentation
  • Stay current with emerging techniques and technologies in data science and machine learning
  • Present findings and recommendations to leadership and business stakeholders
Qualifications
  • Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or related quantitative field
  • 3+ years of professional experience in data science, machine learning, or related analytical role
  • Strong programming skills in Python or R, and proficiency with data manipulation libraries (pandas, numpy, dplyr)
  • Experience building and deploying machine learning models using frameworks such as scikit-learn, Tensor Flow, or Py Torch
  • Solid understanding of statistical methods, experimental design, and hypothesis testing
  • Proficiency with SQL and experience working with relational databases
  • Experience with data visualization tools (Tableau, Power BI, or similar)
  • Strong communication skills with the ability to translate technical concepts to non-technical audiences

Preferred Qualifications

  • Experience with cloud computing platforms (AWS, Azure, GCP)
  • Experience with Snowflake cloud data platform, including:
    • Writing optimized SQL queries for Snowflake’s architecture
    • Leveraging Snowflake’s unique features like Time Travel, Zero-Copy Cloning, and Secure Data Sharing
    • Working with Snowflake’s semi-structured data capabilities (VARIANT, ARRAY, OBJECT types)
    • Using Snowflake’s integration with Python via connectors and Snowpark
    • Experience with Snowflake’s performance optimization techniques
  • Knowledge of big data technologies (Spark, Hadoop)
  • Experience with version control systems (Git) and collaborative development workflows
  • Familiarity with containerization and orchestration tools (Docker, Kubernetes)
  • Experience with NLP, computer vision, or time series analysis
  • Contributions to open-source projects or research publications

Required Technical Skills

  • Programming:
    Python, SQL, R (preferred)
  • Cloud Data Warehousing:
    Snowflake SQL, Snowflake data objects and architecture
  • Machine Learning:
    Classification, regression, clustering, dimensionality reduction
  • Data Processing: ETL pipelines, data cleaning, feature engineering
  • Statistics:
    Hypothesis testing, experimental design, A/B testing
  • Tools:
    Jupyter, Git, Docker…
Position Requirements
10+ Years work experience
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