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Data Science Assistant Jobs in Tennessee (NOW HIRING)

AI and Data Science Engineer III

Nashville, TN · On-site +1

$110K - $132K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms ... knowledge assistants, summarization, and policy question-and-answer solutions using secure ...

Data Scientist

Nashville, TN · On-site

$60K/yr

Data Acquisition, Cleaning & Preprocessing * * Assist in collecting, validating, and preprocessing ... Attend internal workshops and training sessions on data science tools and methodologies. * Stay ...

... KPI's. * Assist in development, maintenance and management of advanced reporting, analytics ... Professional Certifications in AI or Data Science are advantageous. * Experienced in development of ...

$70K - $105K/yr

Responsibilities: Designs, implements, and disseminates advanced analytics and data science ... May write or assist in writing procedures that control reporting needs and processes. Support and ...

... capabilities that assist with data ingestion, feature engineering, data management, and ... Required : • Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems ...

... Assist and guide in analyzing performance, data quality, and design issues during projects. Work ... Bachelor's Degree in Computer Science, Engineering, Data Science, Information Systems, or Business ...

AI Data Engineer - Manager

Nashville, TN

$110K - $132K/yr

You will manage day-to-day delivery with an onshore/offshore team, partnering with data science, ML ... Build tools and capabilities that assist with data ingestion, feature engineering, data management ...

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Data Science Assistant information

What are Data Science Assistants?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

What are the key skills and qualifications needed to thrive as a Data Science Assistant, and why are they important?

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

Is 40 too late for data science?

Data science assistants can enter the field at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is not a barrier if you develop the necessary competencies and stay current with industry trends.

How does a Data Science Assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

What is the difference between Data Science Assistant vs Data Analyst?

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

What is a data scientist assistant?

A data scientist assistant supports data scientists by collecting, cleaning, and analyzing data, often using tools like Python or R. They help prepare reports, build models, and may need knowledge of statistics and data visualization to contribute effectively to data projects.

Is AI replacing data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not replace the need for skilled professionals to interpret results, develop models, and make strategic decisions. Data scientists are increasingly required to work alongside AI tools, focusing on complex problem-solving, model development, and domain expertise. Continuous learning and proficiency in programming languages like Python and tools such as machine learning frameworks remain essential for the role.

Which is better, DS or CS?

For a Data Science Assistant role, both Data Science (DS) and Computer Science (CS) provide valuable skills; DS focuses on data analysis, modeling, and visualization, while CS emphasizes algorithms, programming, and software development. The choice depends on the specific job requirements and your career goals, but familiarity with programming languages like Python or R and understanding of data tools are essential in both fields.
What are the most commonly searched types of Data Science jobs in Tennessee? The most popular types of Data Science jobs in Tennessee are:
What cities in Tennessee are hiring for Data Science Assistant jobs? Cities in Tennessee with the most Data Science Assistant job openings:
Infographic showing various Data Science Assistant job openings in Tennessee as of June 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, 1% Temporary, and 1% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.
Senior Data Scientist

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago


Job description

Position: Senior Data Scientist 

The Senior Data Scientist will be responsible for owning the development and deployment of machine learning models to support operational and clinical use cases at Monogram. This work will be carried out with minimal supervision, contributing to the advancement of Monogram’s data science initiatives. These models will be developed using open-source tools and libraries and may be operationalized as batch or real-time model inference endpoints. The models will utilize a variety of data sources, including healthcare claims, operational data from care management platforms, and EHRs. This position will report to the VP, Data Science with future direct reporting to the Director, Data Science.

Responsibilities
  • Independently develop and deploy machine learning models to support Monogram’s operational and clinical objectives.
  • Conduct data analyses related to model outputs or explore alternative use cases for existing models to enhance reporting and decision-making processes.
  • Engage with program owners to understand program goals, key performance indicators, and operational details to ensure that machine learning models are effectively aligned with program intentions.
  • Create and present machine learning solution proposals to program owners, aiming to secure buy-in and facilitate the implementation of data-driven solutions.
  • Adhere to and promote best practices in software development, data engineering, and machine learning to ensure high-quality and maintainable code.
  • Stay updated with the latest advancements in machine learning and data science, applying new techniques and methodologies to improve model performance and reliability.
  • Maintain and update deployed models, ensuring their accuracy and efficiency over time, and troubleshoot any issues that arise during deployment.
Position Requirements 
  • Bachelor’s degree in data science, Computer Science, Statistics, or a related field; Master’s degree preferred
  • Minimum of five (5) years of experience performing quantitative analyses, preferably within the healthcare claims domain, including experience using Python for machine learning model development and deployment, and SQL, Databricks & PySpark to extract and manipulate data for data engineering tasks.
  • Proficient in developing code and analyses following good software development practices.
  • Experience with version control systems (GIT), CI/CD pipelines, and test-driven development.
  • Familiarity with cloud computing platforms, preferably Azure, for deploying and managing data science solutions.
  • Proven problem-solving abilities and a proactive approach to identifying and addressing business challenges through data-driven solutions, as well as experience presenting technical concepts and models to business and executive stakeholders effectively.
  • Demonstrated teamwork and collaboration skills, with the ability to work effectively in cross-functional teams.
Benefits 
  • Comprehensive Benefits - Medical, dental, and vision insurance, employee assistance program, employer-paid and voluntary life insurance, disability insurance, plus health and flexible spending accounts
  • Financial & Retirement Support – Competitive compensation, 401k with employer match, and financial wellness resources
  • Time Off & Leave – Paid holidays, flexible vacation time/PSSL, and paid parental leave
  • Wellness & Growth – Work life assistance resources, physical wellness perks, mental health support, employee referral program, and BenefitHub for employee discounts 
About Monogram Health

Monogram Health is a leading multispecialty provider of in-home, evidence-based care for the most complex of patients who have multiple chronic conditions. Monogram health takes a comprehensive and personalized approach to a person’s health, treating not only a disease, but all of the chronic conditions that are present - such as diabetes, hypertension, chronic kidney disease, heart failure, depression, COPD, and other metabolic disorders.  

Monogram Health employs a robust clinical team, leveraging specialists across multiple disciplines including nephrology, cardiology, endocrinology, pulmonology, behavioral health, and palliative care to diagnose and treat health issues; review and prescribe medication; provide guidance, education, and counselling on a patient’s healthcare options; as well as assist with daily needs such as access to food, eating healthy, transportation, financial assistance, and more. Monogram Health is available 24 hours a day, 7 days a week, and on holidays, to support and treat patients in their home. 

Monogram Health’s personalized and innovative treatment model is proven to dramatically improve patient outcomes and quality of life while reducing medical costs across the health care continuum.