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Fulltime Data Science Jobs in Tennessee (NOW HIRING)

LP Building Solutions

Data Scientist

Nashville, TN · On-site

... a full-time data scientist to join the data analytics team. Leveraging advanced analytical ... This role combines advanced data science techniques with business partnership to identify ...

Nissan Motor Co., Ltd.

Data Scientist

Smyrna, TN · On-site

Location(s): Smyrna, TN Job Schedule: Full-time, Hybrid (4 days on-site) Education Requirement ... Lead end-to-end delivery of large-scale, cross-functional data science projects. * Facilitate ...

Terminix

Data Scientist, Marketing

Memphis, TN · On-site

$103K - $134K/yr

Benefits Start Day 1 for Full-Time Colleagues - No Waiting Period! For more information about our ... Stay up-to-date with the latest advancements in data science, machine learning, and related ...

University of Rochester

$29.33 - $41.06/hr

Regular Time Type: Full time Scheduled Weekly Hours: 40 Department: 900130 URMC Finance Decision ... Creates and implements data science solutions to support analytical efforts and expand dashboard ...

Nissan Motor Co., Ltd.

Data Engineer

Franklin, TN · On-site

$113K - $135K/yr

Franklin, TN Job Schedule: Full time, hybrid (M-TH onsite, F remote) Education Requirement ... Collaborate with Data Scientists and BI teams * Support MLOps and analytics workloads * Document AI ...

Nissan Motor Manufacturing UK

Data Engineer

Franklin, TN · Hybrid

$113K - $135K/yr

Franklin, TN Job Schedule: Full time, hybrid (M-TH onsite, F remote) Education Requirement ... Collaborate with Data Scientists and BI teams * Support MLOps and analytics workloads * Document AI ...

University of Rochester

$86K - $130K/yr

Regular Time Type: Full time Scheduled Weekly Hours: 40 Department: 900130 URMC Finance Decision ... data science concepts to lay/nonexpert audiences required The University of Rochester is committed ...

Sonsoft Inc

Sr. Data Scientist

Memphis, TN

Senior data scientist. * Research various analytical approaches * Recommend and develop ... This is a Full-Time & Permanent job opportunity. * Only US Citizen , Green Card Holder , GC-EAD ...

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All JobsFulltime Data Science JobsFulltime Data Science Jobs in Tennessee

Fulltime Data Science information

What is the difference between Fulltime Data Science vs Part-time Data Science?

AspectFulltime Data SciencePart-time Data Science
Work HoursTypically 35-40 hours/weekLess than 20 hours/week
Employment TypePermanent, full benefitsTemporary or flexible arrangement
CredentialsOften requires a degree in Data Science, Statistics, or related fieldsSame credentials as fulltime, but may vary based on project needs
Work EnvironmentOffice or remote, integrated with teamFlexible, often remote or freelance

Fulltime Data Science roles involve consistent, long-term employment with comprehensive benefits, requiring full credentials and offering a stable work environment. Part-time Data Science positions provide flexibility and shorter commitments, suitable for project-based work or supplementary income, with similar credential requirements but fewer benefits.

What are popular job titles related to Fulltime Data Science jobs in Tennessee? For Fulltime Data Science jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Fulltime Data Science jobs in Tennessee look for? The top searched job categories for Fulltime Data Science jobs in Tennessee are:
What cities in Tennessee are hiring for Fulltime Data Science jobs? Cities in Tennessee with the most Fulltime Data Science job openings:
Fulltime Data Science jobs near you
Data Scientist

Data Scientist

LP Building Solutions

Nashville, TN • On-site

Full-time

Posted 14 days ago

Job description

Data Scientist
Req Id: 12517
Job Location: Home Office LP, Nashville
Posting Start Date: 6/4/26
Work Environment: Hybrid
Job Description:
Job Purpose
LP Building Solutions, a large specialty building products manufacturer, is looking for a full-time data scientist to join the data analytics team. Leveraging advanced analytical techniques, statistical modeling, and/or machine learning, you will partner with the business to uncover opportunities, optimize performance, and drive data-informed outcomes. This role will partner closely with marketing, sales, operations, supply chain, corporate, and finance teams to identify opportunities, develop predictive and prescriptive models, and deliver actionable insights that improve revenue growth, operational efficiency, and margin performance. This role combines advanced data science techniques with business partnership to identify opportunities, solve complex problems, and generate insights for decision support.
The ideal candidate combines strong technical expertise in statistical modeling and advanced analytics with the ability to translate complex data into clear, business-relevant insights for marketing and sales teams. This individual will work with large, complex datasets spanning manufacturing, distribution, pricing, and customer behavior. This role requires a strong blend of analytical rigor and business acumen, with the ability to work cross-functionally and influence stakeholders. While this role does not require hands-on data engineering responsibilities, it demands close collaboration with the Data Engineering team. Candidates should have a solid understanding of core data engineering concepts to effectively partner, translate business needs, and ensure alignment across data workflows and infrastructure.
In this position you will have the opportunity to:
  • Complete end-to-end data science initiatives, from business problem framing and data exploration through model development, validation, deployment partnership, and performance monitoring.
  • Work directly with internal and external customers to define success criteria, hypotheses, and measurable outcomes. Translate the business needs into analytics/reporting requirements to support executive decisions and workflows with required information.
  • Design, build, and evaluate predictive, prescriptive, and statistical models that improve decision-making, operational efficiency, customer outcomes, or financial performance
  • Design and evaluate experiments to test hypotheses, measure impact, and guide decisions (e.g., A/B, Multivariate, simulation, scenario, Quasi, etc.)
  • Apply advanced analytical methods such as machine learning, forecasting, optimization, causal inference, and experimentation to solve high-value business problems.
  • Proactively identify trends and patterns and generates insights for business units and senior leadership
  • Work with the IT Data Engineering team to integrate data from multiple sources including CRM, ERP, Operational systems, web analytics, and third-party datasets for analysis
  • Research and implement cutting-edge techniques and tools in machine learning/artificial intelligence to make data analysis more efficient
  • Present insights and recommendations to stakeholders in a clear, business-focused manner. You will need to simplify complex methodologies into actionable business insights
  • Establish processes and tools that monitor, analyze and continuously improve model performance and data accuracy
  • Partner with the Analytics leadership team to align initiatives and strategy. Contribute to enterprise analytics roadmap and best practices.
  • Support other Analytics team members by providing technical guidance, peer review, and thought partnership.

What do I need to be successful?
  • 5+ years of progressive experience supporting marketing and sales teams in data science, advanced analytics, or a closely related field
  • Experience in the development of Machine Learning models and AI frameworks
  • Experience working with data visualization and business intelligence tools to communicate insights effectively. (e.g., Tableau, Power BI, or similar tools)
  • Experience working with enterprise data platforms (e.g., Snowflake, Databricks, Cloudera, BigQuery)
  • Experience working with data from large enterprise applications (e.g., ERP, CRM or Operational systems)
  • Preferred experience working with SAP (S/4 HANA, ECC, BTP, etc.)
  • Preferred experience working with Cloud platforms (AWS, Azure, or GCP)
  • Preferred experience in text analytics, image recognition, graph analysis, or other specialized ML techniques, such as deep learning
  • Preferred experience in manufacturing, building products, or construction-related industries.
  • Fluency in multiple analytical programming languages such as Python & SQL (required), R (optional)
  • Demonstrated experience developing and validating statistical models, machine learning algorithms, and advanced analytical solutions using large, complex datasets.
  • Strong competency in Statistical & Quantitative Methods (e.g., Hypothesis testing, regression, probability theory, experimental design etc)
  • Demonstrated experience and comfortable with experimentation and causal analysis.
  • Demonstrated experience with experimental design, model evaluation, and performance measurement.
  • Strong understanding of data pipelines, ETL processes, and data architecture
  • Proven success in supervised and unsupervised learning (e.g., regression, classification, clustering)
  • Strong understanding of AI, its potential roles in solving business problems, and the future trajectory of generative AI models
  • Excellent presentation, communication and stakeholder management skills, with the ability to explain technical concepts in business terms to a diverse audience with a wide range of understanding
  • Highly self-motivated with proven ability to operate autonomously. managing multiple priorities, in a fast-paced environment
  • Willingness and ability to learn new technologies on the job with a continuous learning and innovation mindset

Education
  • Bachelor's degree in computer science, mathematics, data science, statistics, or a related quantitative field.
  • Master's degree preferred.

Work Environment
  • This position may be remote, working in a home office environment, but Nashville, TN candidates are strongly preferred.
  • Occasional travel up to 15% of time.
  • Occasional exposure to a plant environment.

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