Summary
MathWorks has a hybrid work model that enables staff members to split their time between office and home. The hybrid model provides the advantage of having both in-person time with colleagues and flexible at-home life optimizations. Learn More: https://www.mathworks.com/company/jobs/resources/applying-and-interviewing.html#onboarding.
The Data Science Engineer will work within the Development organization to turn data into insights and solutions that guide product decisions, improve software development processes, and create business value. The role involves leading projects across the full data science lifecycle, from understanding business needs and building data pipelines to deploying analytics solutions and helping teams make informed decisions. Success requires not only strong analytical and technical skills, but also the ability to influence stakeholders and help teams turn insights into action.
MathWorks nurtures growth, appreciates inclusivity, encourages initiative, values teamwork, shares success, and rewards excellence.
Responsibilities
- Lead initiatives that increase adoption of data-informed decision-making and influence change across Development
- Partner with Subject Matter Experts (SMEs) and Development teams to define success metrics and evaluate the impact of product, process, and business initiatives using data
- Design, build, and maintain reliable data pipelines for reporting, analytics, and modeling using data stored on cloud platforms such as AWS and Snowflake
- Analyze quantitative and qualitative data using statistical, machine learning, and LLM-based techniques
- Develop and maintain dashboards and reports (Power BI and/or MATLAB) to communicate key insights to stakeholders
- Evaluate and implement AI-assisted and agent-based systems to enhance data science workflows
Minimum Qualifications
- A bachelor's degree and 6 years of professional work experience (or a master's degree and 3 years of professional work experience, or a PhD degree, or equivalent experience) is required.
Additional Qualifications
- Strong data engineering skills, including knowledge of ETL processes and experience building data pipelines in production on AWS and Snowflake
- Strong understanding of metrics design, statistics, probability, machine learning, and LLM-based techniques
- Experience programming in SQL, Python, and/or MATLAB
- Familiarity with data visualization tools such as Power BI or Tableau
- Strong partnership, facilitation, and communication skills
