Data Scientist

Nissan • Smyrna, TN

11d • Hybrid

About The Position

Shape the Future of Mobility at Nissan: Launch Your Career, Drive Innovation Come Drive Innovation with Us. We are currently looking for a Data Scientist to join our team in Smyrna, TN. In this role, you will serve as a highly independent contributor responsible for leading large, cross-functional data science initiatives that deliver measurable business value across the MZK organization. The Data Scientist owns end-to-end execution—from problem framing and solution design to model development, validation, and deployment—while partnering closely with stakeholders, product owners, and technical teams. The Data Scientist combines strong technical expertise in statistical modeling and machine learning with solid business acumen to translate complex operational challenges into scalable analytical solutions. The role operates with a high degree of autonomy in project execution and decision-making, while collaborating with senior data scientists on more complex or ambiguous problems. In addition to hands-on delivery, this role contributes to team capability by mentoring junior members and reinforcing best practices, though it does not define enterprise-wide standards or long-term data science strategy. A Day in the Life: Partner with stakeholders and data product owners to translate complex or ambiguous business challenges into structured data science use cases. Lead exploratory data analysis (EDA), data preparation, and feature engineering across diverse data sets. Design, develop, and validate predictive, descriptive, and forecasting models using advanced statistical and machine learning techniques. Apply best practices such as cross-validation, backtesting, and drift monitoring to ensure model reliability. Build end-to-end analytical solutions using tools like Python, R, SQL, Power BI/Tableau, and cloud platforms (AWS, Snowflake). Collaborate with IS/IT and data engineering teams to prepare data pipelines, integrate data sources, and support scalable deployment. Translate technical findings into clear, actionable insights for both technical and non-technical audiences. Lead proof-of-concept (POC) initiatives to evaluate emerging technologies and drive innovation Contribute to governance, documentation, and best practices to ensure consistency and reproducibility. Develop domain expertise across MZK functions to enhance solution relevance and impact. On the project side, you will: Lead end-to-end delivery of large-scale, cross-functional data science projects. Facilitate solution design workshops, technical reviews, and stakeholder discovery sessions. Define project scope, timelines, and deliverables while managing dependencies and risks. Create structured documentation including workflows, data dictionaries, and modeling artifacts. Monitor progress, ensure alignment to business objectives, and proactively address challenges.

Requirements

• Bachelor’s degree in Business Analytics, Data Science, Operations Research, Mathematics, Statistics, or related field (or equivalent certification).
• 3+ years of hands-on experience in data science, machine learning, or advanced analytics.
• Strong expertise in Statistical modeling, machine learning, and predictive analytics.
• Strong expertise in Python, R, SQL, and data visualization tools (Power BI, Tableau).
• Strong expertise in Cloud platforms such as AWS, Snowflake, or Azure.
• Experience designing and validating models using techniques such as time-series cross-validation and backtesting.
• Proven ability to work with large, complex datasets (structured and unstructured).
• Demonstrated success delivering cross-functional data science projects with measurable impact.
• Strong project management skills, including scoping, planning, and risk mitigation.
• Ability to translate complex problems into analytical solutions and communicate insights clearly.
• Highly organized, detail-oriented, and capable of managing multiple priorities.

Nice To Haves

• Master’s degree (MS/MBA) in Analytics, Statistics, Mathematics, Operations Research, or related field.
• 5+ years of data science experience.
• Experience with big data tools and platforms (e.g., Hadoop, Spark)
• Familiarity with Agile methodologies.
• Experience with MLOps tools and model deployment frameworks
• Strong cross-functional business acumen, especially within manufacturing, supply chain, or procurement domains.
• Experience collaborating with IS/IT and data engineering teams on data architecture and pipelines.
• Strong communication and stakeholder management skills across all levels of the organization.
• Proven experience leading teams or large-scale initiatives with multiple workstreams.

Responsibilities

• Partner with stakeholders and data product owners to translate complex or ambiguous business challenges into structured data science use cases.
• Lead exploratory data analysis (EDA), data preparation, and feature engineering across diverse data sets.
• Design, develop, and validate predictive, descriptive, and forecasting models using advanced statistical and machine learning techniques.
• Apply best practices such as cross-validation, backtesting, and drift monitoring to ensure model reliability.
• Build end-to-end analytical solutions using tools like Python, R, SQL, Power BI/Tableau, and cloud platforms (AWS, Snowflake).
• Collaborate with IS/IT and data engineering teams to prepare data pipelines, integrate data sources, and support scalable deployment.
• Translate technical findings into clear, actionable insights for both technical and non-technical audiences.
• Lead proof-of-concept (POC) initiatives to evaluate emerging technologies and drive innovation
• Contribute to governance, documentation, and best practices to ensure consistency and reproducibility.
• Develop domain expertise across MZK functions to enhance solution relevance and impact.
• Lead end-to-end delivery of large-scale, cross-functional data science projects.
• Facilitate solution design workshops, technical reviews, and stakeholder discovery sessions.
• Define project scope, timelines, and deliverables while managing dependencies and risks.
• Create structured documentation including workflows, data dictionaries, and modeling artifacts.
• Monitor progress, ensure alignment to business objectives, and proactively address challenges.

Benefits

• Comprehensive Benefits Package, including medical, mental health, parental leave, retirement savings
• Unique Nissan perks, including discounts on lease vehicles as part of our Employee Lease Program and a Vehicle Purchase Program (VPP).
• Career Growth and Continuous Learning Opportunities: Benefit from diverse career paths, cross-departmental moves, and innovative learning platforms.
• Enhance your skills through seminars, leadership training, and tuition reimbursement programs.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level