Data Scientist

About the role

Shape the Future of Mobility at Nissan: Launch Your Career, Drive Innovation

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.
• 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.

Qualifications

• 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.
• Experience with 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.

Skills

• Statistical modeling
• Machine learning
• Predictive analytics
• Python
• R
• SQL
• Data visualization tools (Power BI, Tableau)
• Cloud platforms (AWS, Snowflake)
• Big data tools and platforms (Hadoop, Spark)
• Agile methodologies
• MLOps tools and model deployment frameworks
• Manufacturing, supply chain, or procurement domains
• Collaboration with IS/IT and data engineering teams
• Communication and stakeholder management skills
• Project management skills

Benefits

Comprehensive Benefits Package, including medical, mental health, parental leave, retirement savings, and unique Nissan perks such as discounts on lease vehicles and a Vehicle Purchase Program (VPP).