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Data Science Associate Jobs in Tennessee (NOW HIRING)

... data science. Supports and helps drive an innovative culture * Suggests new and useful ideas or ... For Digital Insights Lab Associates: Performs key tasks in monitoring, troubleshooting and ...

Digital Innovation Engineer

Memphis, TN · On-site

$132K/yr

... data science. Supports and helps drive an innovative culture * Suggests new and useful ideas or ... For Digital Insights Lab Associates: Performs key tasks in monitoring, troubleshooting and ...

... data science. Supports and helps drive an innovative culture * Suggests new and useful ideas or ... For Digital Insights Lab Associates: Performs key tasks in monitoring, troubleshooting and ...

... data science. Supports and helps drive an innovative culture * Suggests new and useful ideas or ... For Digital Insights Lab Associates: Performs key tasks in monitoring, troubleshooting and ...

... data science. Supports and helps drive an innovative culture * Suggests new and useful ideas or ... For Digital Insights Lab Associates: Performs key tasks in monitoring, troubleshooting and ...

Digital Innovation Engineer

Memphis, TN · On-site

$132K/yr

... data science. Supports and helps drive an innovative culture * Suggests new and useful ideas or ... For Digital Insights Lab Associates: Performs key tasks in monitoring, troubleshooting and ...

... Associate] is a plus - Designing and implementing thorough data architecture strategies ... Engineering, Data Science, and Data Governance - Architecting and implementing cloud-based ...

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Data Science Associate information

See Tennessee salary details

$52.2K

$61.8K

$117.1K

How much do data science associate jobs pay per year?

As of Jul 2, 2026, the average yearly pay for data science associate in Tennessee is $61,753.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,500.00 and $54,000.00 per year, depending on experience, location, and employer.

How does a Data Science Associate typically collaborate with other departments or teams within an organization?

Data Science Associates frequently work cross-functionally, partnering with teams such as engineering, product management, and business analytics to understand project requirements, share findings, and implement data-driven solutions. Collaboration often involves translating complex data results into actionable insights for non-technical stakeholders, ensuring alignment on project goals and deliverables. This role requires strong communication skills, as associates routinely participate in meetings, present analyses, and gather feedback to refine their models or analyses. Effective teamwork helps ensure that data science initiatives support broader business objectives.

Is 40 too late for data science?

Age is not a barrier to becoming a data science associate; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Is an Associates in data science worth it?

An associate's degree in data science can provide foundational skills in data analysis, programming, and statistics, which may help entry-level candidates qualify for junior data science roles. However, many employers prefer candidates with a bachelor's degree or higher, and practical experience or certifications in tools like Python, R, or SQL can enhance job prospects. The value depends on career goals and the specific requirements of potential employers.

What can I do with an associate's degree in data science?

A Data Science Associate with an associate's degree can work as a data analyst, supporting data collection, cleaning, and basic analysis using tools like Excel, SQL, and Python. They often assist in generating reports, visualizations, and insights under supervision, and may pursue certifications to enhance their skills for more advanced roles.

What are Data Science Associates?

Data Science Associates are early-career professionals who support data-driven projects by collecting, cleaning, analyzing, and interpreting large datasets. They typically work under the guidance of more experienced data scientists and help build predictive models, generate reports, and provide insights to inform business decisions. This role often requires proficiency in programming languages like Python or R, familiarity with statistical methods, and strong problem-solving skills. Data Science Associates play a crucial part in transforming raw data into actionable information for organizations.

What is the role of an associate data scientist?

An associate data scientist supports data analysis and modeling tasks by cleaning and processing data, developing algorithms, and creating visualizations. They often work under supervision to assist in building predictive models and may use tools like Python, R, or SQL to analyze data and generate insights.

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

To thrive as a Data Science Associate, you need strong analytical skills, a solid foundation in statistics and mathematics, and proficiency in programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with machine learning frameworks, data visualization tools, and database systems such as SQL is typically required. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate complex data insights into actionable business strategies. These skills are vital for extracting meaningful value from data and supporting data-driven decision-making within organizations.

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

AspectData Science AssociateData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; often no advanced certifications required
Work EnvironmentCollaborates with data scientists and engineers; involved in building models and algorithmsFocuses on data collection, cleaning, and reporting; supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for data-driven projectsCommon across various industries for business insights and reporting

The Data Science Associate role typically involves more technical work like building models and applying machine learning, whereas Data Analysts focus on interpreting data and creating reports. Both roles require strong analytical skills, but Data Science Associates often have a deeper understanding of programming and statistical modeling.

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 are popular job titles related to Data Science Associate jobs in Tennessee? For Data Science Associate jobs in Tennessee, the most frequently searched job titles are:
What cities in Tennessee are hiring for Data Science Associate jobs? Cities in Tennessee with the most Data Science Associate job openings:
Data Solutions Architect

Data Solutions Architect

Laksan Technologies

Nashville, TN • On-site

Contractor

Posted yesterday


Job description

Description:

The Data Architect for the General Sessions Data Repository will play a pivotal role in strategically designing, developing, and implementing the data model for this critical enterprise-level data warehouse. This repository integrates diverse data sources from General Sessions courts across Tennessee into a unified platform to enable comprehensive reporting and analysis. This individual will be the primary advocate for data modeling methodologies and data processing best practices within the context of the repository. The Data Architect will work across conceptual, logical, business areas (court operations), and application layers to ensure robust and efficient data architecture that supports the Administrative Office of the Court’s (AOC) strategic goals for data-driven decision-making.

Responsibilities:

Strategy & Planning:

·         Develop and deliver a long-term strategic vision and standards for the data architecture of the General Sessions Data Repository, in collaboration with data users, court personnel, IT teams, and other stakeholders within the AOC.

·         Create short-term tactical solutions and an overall data management roadmap specifically for the General Sessions Data Repository initiative.

·         Establish and enforce processes for governing the identification, collection, and use of metadata related to court data; implement measures to ensure metadata accuracy and validity within the repository.

·         Define methods and procedures for tracking data quality, completeness, consistency, and identifying areas for improvement within the integrated data.

·         Conduct data capacity planning, lifecycle management, usage requirements analysis, and feasibility studies specific to the General Sessions Data Repository.

·         Contribute to strategies and plans for data security, backup, disaster recovery, business continuity, and archiving related to the repository data.

·         Ensure that data strategies and architectures for the General Sessions Data Repository adhere to relevant state and federal regulations and AOC policies.

Acquisition & Deployment:

·         Ensure the successful integration of various data sources into the General Sessions Data Repository.

·         Liaise with vendors and service providers for any tools or services related to the data repository, ensuring they align with the AOC's needs.

Operational Management:

·         Assess and determine governance, stewardship, and frameworks for managing data within the General Sessions Data Repository.

·         Develop and promote data management methodologies and standards specific to data warehousing and reporting within the AOC environment.

·         Select and implement appropriate tools, software, applications, and systems to support the data technology goals of the General Sessions Data Repository.

·         Oversee the mapping of data sources, data movement processes (ETL/ELT), interfaces, and analytics related to the repository, with a strong focus on ensuring data quality and accuracy.

·         Collaborate closely with project managers, business analysts, and court personnel on all projects involving data from the General Sessions Data Repository.

·         Address data-related problems concerning systems integration, data compatibility across disparate court systems, and multi-platform integration into the data warehouse.

·         Act as a leader and advocate for data management best practices related to the General Sessions Data Repository, potentially providing guidance to other staff involved in data-related activities.

·         Develop and implement key components and testing criteria to guarantee the fidelity and performance of the General Sessions Data Repository architecture.

·         Document the data architecture and environment of the General Sessions Data Repository to maintain a current and accurate understanding of the data landscape.

·         Identify and develop opportunities for data reuse, migration, or retirement within the context of the General Sessions Data Repository.

·         Data Governance and Security: Ensuring data quality, accuracy, consistency, and security within the data warehouse. 

Position Requirements:

Formal Education & Certification:

  • ·       Bachelor's degree in computer science, information systems, data science, or a related field.
  • ·       Relevant certifications in data warehousing, data modeling, or database administration (e.g., Certified Data Management Professional (CDMP), AWS Certified Data Analytics – Specialty, Microsoft Certified: Azure Data Engineer Associate) are a plus.

Knowledge & Experience:

  • ·      5 years of work experience as a data architect, data warehouse architect, or similar role, with a focus on data integration and reporting.
  • ·      Hands-on experience with data architecting, data modeling (dimensional modeling, relational modeling), ETL/ELT processes, and requirements gathering/analysis, preferably within a complex data environment.
  • ·      Direct experience in implementing data management processes, procedures, and decision support systems, ideally within a government or judicial context.
  • ·      Database Administration and Performance Tuning: Knowledge of database management systems and techniques for optimizing performance.
  • ·      Strong understanding of relational data structures, theories, principles, and practices, as well as data warehousing concepts.
  • ·      Demonstrated expertise with data warehouse design, development, and data and information system lifecycle methodologies.
  • ·      Experience with business requirements analysis, entity-relationship modeling, dimensional modeling, database design for reporting and analytics, and the creation of reporting structures.
  • ·      Ability to manage data migration into a data warehouse environment.
  • ·      Experience with various database platforms (e.g., Microsoft SQL Server, Oracle)
  • ·      Understanding of data security principles and best practices relevant to sensitive data.
  • ·      Experience with data processing flowcharting techniques and data flow diagrams.
  • ·      Proven ability to work independently and collaboratively within a team environment.

Personal Attributes:

  • ·         Excellent written and oral communication skills, with the ability to clearly articulate complex technical concepts to both technical and non-technical audiences.
  • ·         Strong presentation and interpersonal skills, with the ability to effectively communicate with court personnel and other stakeholders.
  • ·         Ability to present technical ideas in a user-friendly language.
  • ·         Strong analytical and problem-solving skills.
  • ·         Attention to detail and a commitment to data quality.