Data Scientist

Nissan Motor Corporation•Smyrna, TN

7d•Hybrid

About The Position

We are currently looking for a Data Scientist to join our team in Smyrna, TN. In this role, you'll lead data science projects that help solve complex business and operational challenges across the organization. You'll work closely with business stakeholders and technical teams to identify opportunities, develop analytical and machine learning solutions, and drive projects from initial concept through deployment. The position requires a strong mix of technical expertise and business understanding, as well as the ability to work independently, influence cross-functional teams, and mentor junior team members while delivering measurable business value.

Requirements

Bachelor’s degree in Business Analytics, Data Science, Operations Research, Mathematics, Statistics, or related field (or equivalent certification).
5+ 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 back testing.
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.
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, back testing, 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.