Business Data Scientist – Advanced Analytics

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What we offer:

Group Summary:

We are looking for a Data Scientist who can work closely with business stakeholders to design, build, and operationalize advanced forecasting and analytics solutions across various business functions like procurement, sales, finance, treasury, or quality. This role combines classical machine learning with emerging GenAI/LLM techniques to deliver high-impact insights for senior leadership. You will manage models end-to-end, converting strategic business questions into scalable, production-ready solutions that support decision making and early-warning capabilities.

Key Responsibilities

• Collaborate with business teams to translate domain problems (e.g., spend, sales, cash flow, quality trends) into analytical and forecasting use cases.

• Own model development from concept to deployment, including data preparation, feature engineering, model design, testing, and monitoring on Databricks.

• Build time-series, regression, anomaly detection, and early-warning models for leadership reporting and high-impact business decisions.

• Identify and apply GenAI/LLM approaches—such as narrative generation, scenario simulation, or hybrid modeling—where they bring clear value.

• Work closely with Data Engineering to define data requirements and ensure high-quality, reliable pipelines.

• Communicate analytical outcomes and recommendations in clear business terms for executive stakeholders.

• Apply MLOps practices (MLflow, Model Registry, workflows) for reproducibility and operational robustness.

• Support the maturation of the organization’s AI/ML landscape by contributing patterns, best practices, and model lifecycle improvements.

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, Economics, or related field.

• 4–6 years of experience in data science with a track record of delivering end-to-end forecasting or business-focused ML solutions.

• Strong proficiency in Python and SQL; experience with Databricks for analytics, ML, and data pipelines.

• Solid grounding in time-series and classical ML methods, with experience deploying models in production environments.

• Strong communication and stakeholder engagement skills, with the ability to collaborate with non-technical business leaders.

• Experience applying MLOps practices (reproducibility, CI/CD, monitoring, lifecycle management).

Preferred Skills

• Experience working with business functions like sales, finance, procurement, treasury, or quality analytics in a manufacturing or enterprise context.

• Familiarity with GenAI/LLM techniques and practical application to business workflows.

• Exposure to product-centric work with cross-functional teams.

• Knowledge of visualization tools such as Power BI or Tableau.

• Understanding of manufacturing, automotive, or large enterprise business processes.

Awareness, Unity, Empowerment:

At Magna, we believe that a diverse workforce is critical to our success. That’s why we are proud to be an equal opportunity employer. We hire on the basis of experience and qualifications, and in consideration of job requirements, regardless of, in particular, color, ancestry, religion, gender, origin, sexual orientation, age, citizenship, marital status, disability or gender identity. Magna takes the privacy of your personal information seriously. We discourage you from sending applications via email or traditional mail to comply with GDPR requirements and your local Data Privacy Law.

AI-Assisted Screening Disclosure

As part of our commitment to a fair, consistent, and efficient recruitment process, we may use artificial intelligence (AI) tools to assist in the initial screening of applications submitted through our Workday system. These tools help identify qualifications and experience that align with the role requirements. Please note that AI is used solely to support our recruiters. Final decisions are always made by the hiring manager and the hiring team. Importantly, no applicant data is shared externally through these AI tools. All information remains securely within our systems and is handled in accordance with our privacy and data protection policies.

Under conditions defined by applicable law, you may have the right to request an explanation of how AI is used to support decision-making.

If you have any questions or concerns about this process, feel free to contact our Talent Attraction team.