At Morningstar, we’re driven by a singular mission: to empower investors with high-quality research, data, and tools that help them make confident, informed decisions. Our Research Group is a cornerstone of this effort, providing independent analysis on individual securities, funds, and markets. We are looking for a dynamic Data Scientist to join our team, bringing cutting-edge Artificial Intelligence (AI) and Machine Learning (ML) solutions to transform data collection and analytics in the investment research space.
About the Role:
As a Data Scientist at Morningstar, you'll play a crucial role in integrating AI and ML solutions into our Data Collections software, APIs, and data products. You’ll work closely with cross-functional teams from Technology, Data, Research, and Products to drive forward innovation and ensure the seamless transition of AI prototypes into fully operational, scalable solutions. Your work will directly contribute to enhancing the investment decision-making process for our clients by improving the efficiency and accuracy of data collection and processing.
What You’ll Do:
- Lead Automation Initiatives: Use NLP techniques to automate manual data collection processes, tackling tasks like text classification, Named Entity Recognition (NER), and other NLP challenges.
- Collaborate Across Teams: Partner with data analysts, researchers, and engineers to design and implement AI-driven solutions that solve complex business problems.
- Implement End-to-End AI/ML Solutions: From conceptualizing AI models to their deployment, you’ll ensure smooth integration of AI services into Morningstar's financial products.
- Innovate and Improve: Continuously explore new technologies and approaches to improve automation and increase data collection efficiency.
- Contribute to Research & Development: Stay at the forefront of AI/ML advancements by researching cutting-edge technologies and proposing solutions to existing challenges.
- Mentorship and Team Collaboration: Provide guidance to Machine Learning Data Analysts (MLDAs), participate in team brainstorming sessions, and contribute to the overall growth of the AI team.
- Follow Best Practices: Maintain high standards for development processes, estimation, planning, and reporting.
What We’re Looking For:
- Education: Ph.D. in Engineering, Computer Science, Statistics, or a related field; OR 2+ years of industrial experience in a data science role, specifically with NLP tasks, if you have a Master's or lower degree.
- Technical Expertise:
- Proficiency in Python, with hands-on experience using libraries such as NumPy, pandas, scikit-learn, NLTK, PyTorch, and TensorFlow.
- Deep understanding of ML/AI algorithms (e.g., regression, random forests, gradient boosting, transformers, BERT, open-source LLMs).
- Familiarity with SQL for data manipulation and analysis.
- Experience with DevOps tools (e.g., Sagemaker, Git, Jenkins) and cloud services like Amazon AWS (e.g., Lambda, Sagemaker, EC2) is desirable.
- Preferred Experience:
- Experience with generative AI and finetuning large language models (LLMs).
- Familiarity with data cleaning and munging techniques, as well as data visualization.
- Exposure to financial data such as mutual funds, fixed income, and equities is a plus.
- Communication & Collaboration Skills:
- Strong written and verbal communication abilities, capable of presenting complex data insights in a clear and accessible manner to non-technical stakeholders.
- Ability to work independently and proactively, contributing both to your team and across Morningstar.
Why Morningstar?
- Innovative Work Environment: Work on cutting-edge AI/ML solutions within the investment research space, tackling real-world challenges in a fast-paced, dynamic environment.
- Career Development: Mentorship and opportunities to further your career with leadership coaching, education stipends, tuition reimbursement, and formal mentorship programs.
- Work-Life Balance: Enjoy our hybrid work policy that balances remote flexibility with in-person collaboration. Plus, benefit from Trust-Based Time Off, a 6-week Paid Sabbatical Program, and Paid Family Care Leave.
- Comprehensive Benefits Package:
- Financial Health: Generous 401(k) match, stock ownership options, and life insurance.
- Physical Health: Comprehensive health plans (medical, dental, vision), HSA contributions, and wellness incentives.
- Emotional Health: Mental health support, sabbaticals, family leave, and leadership coaching.
- Social Impact: Charitable matching programs, paid volunteer days, and active employee resource groups.
