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Job Title: Data Scientist
Location: Remote (Nashville, TN strongly preferred)
Job-Type: Full-Time
Employment Eligibility: Gravity cannot transfer nor sponsor a work visa for this position. Applicants must be eligible to work in the U.S. for any employer directly (we are not open to contract or “corp to corp” agreements).
Role Overview:
We are 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. 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. 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.
Responsibilities:
- 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 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 generate insights for business units and senior leadership
- Partner 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, simplifying complex methodologies into actionable insights
- Establish processes and tools that monitor, analyze, and continuously improve model performance and data accuracy
- Partner with Analytics leadership to align initiatives and strategy; contribute to the enterprise analytics roadmap and best practices
- Support other Analytics team members by providing technical guidance, peer review, and thought partnership
Requirements:
- 5+ years of progressive experience in data science, advanced analytics, or a closely related field, with a strong preference supporting marketing or commercial teams
- Experience in the development of machine learning models and AI frameworks
- Experience working with data visualization and business intelligence tools (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)
- Fluency in Python and 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 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
- 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
- Bachelor’s degree in computer science, mathematics, data science, statistics, or a related quantitative field (Master’s degree preferred)
- Occasional travel up to 15% of time
- Occasional exposure to a plant environment
Preferred Qualifications:
- Experience working with SAP (S/4 HANA, ECC, BTP, etc.)
- Experience working with cloud platforms (AWS, Azure, or GCP)
- Experience in text analytics, image recognition, graph analysis, or other specialized ML techniques (e.g., deep learning)
- Experience in manufacturing, building products, or construction-related industries
Job Title: Data Scientist
Location: Remote (Nashville, TN strongly preferred)
Job-Type: Full-Time
Employment Eligibility: Gravity cannot transfer nor sponsor a work visa for this position. Applicants must be eligible to work in the U.S. for any employer directly (we are not open to contract or “corp to corp” agreements).
Role Overview:
We are 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. 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. 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.
Responsibilities:
- 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 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 generate insights for business units and senior leadership
- Partner 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, simplifying complex methodologies into actionable insights
- Establish processes and tools that monitor, analyze, and continuously improve model performance and data accuracy
- Partner with Analytics leadership to align initiatives and strategy; contribute to the enterprise analytics roadmap and best practices
- Support other Analytics team members by providing technical guidance, peer review, and thought partnership
Requirements:
- 5+ years of progressive experience in data science, advanced analytics, or a closely related field, with a strong preference supporting marketing or commercial teams
- Experience in the development of machine learning models and AI frameworks
- Experience working with data visualization and business intelligence tools (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)
- Fluency in Python and 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 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
- 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
- Bachelor’s degree in computer science, mathematics, data science, statistics, or a related quantitative field (Master’s degree preferred)
- Occasional travel up to 15% of time
- Occasional exposure to a plant environment
Preferred Qualifications:
- Experience working with SAP (S/4 HANA, ECC, BTP, etc.)
- Experience working with cloud platforms (AWS, Azure, or GCP)
- Experience in text analytics, image recognition, graph analysis, or other specialized ML techniques (e.g., deep learning)
- Experience in manufacturing, building products, or construction-related industries
To Apply for this Job Click Here
Equal Employment Opportunity Statement
Gravity IT Resources is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other legally protected characteristic. All employment decisions are based on qualifications, merit, and business needs.