> Markdown version of [/jobs/ext/3874218-senior-data-scientist](https://www.wearedevelopers.com/jobs/ext/3874218-senior-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior Data Scientist

- **Company:** Mitchell International, Inc.
- **Location:** San Diego, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $110,000.0 - $135,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Amazon Web Services, Data Analysis, Computer Vision, Microsoft Azure, Big Data, Cloud Database, Computer Programming, Data Cleansing, Extract Transform Load (ETL), Data Security, Data Visualization, Relational Databases, R (Programming Language), Apache Hadoop, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, NumPy, Open Source Technology, Performance Tuning, Power BI, Tensorflow, SQL Databases, Tableau (Software), Data Processing, Google Cloud, Cloud Platform System, Feature Engineering, Pytorch, Snowflake, Apache Spark, Jupyter, Git, Pandas, Matplotlib, Containerization, Semi-structured Data, Scikit Learn, Kubernetes, Information Technology, Data Objects, Software Version Control, Docker
- **Published:** October 22, 2026
- **Apply:** https://www.jofdav.com/jobs/60232751-senior-data-scientist

## About the Role

* 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, TensorFlow, or PyTorch
 * 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 (preferred)
 * Visualization: Matplotlib, Seaborn, ggplot2, Tableau, PowerBI
*

Soft Skills

 * Problem-solving and analytical thinking
 * Excellent written and verbal communication
 * Collaboration and teamwork
 * Attention to detail
 * Time management and prioritization
 * Continuous learning mindset

## Description

* 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