Job Title

The Group:Morningstars Research group provides independent analysis on individual securities, funds, markets, and portfolios. The Research group also provides data on hundreds of thousands of investment offerings, including stocks, mutual funds, and similar vehicles, along with real-time global market data on millions of equities, indexes, futures, options, commodities, and precious metals, in addition to foreign exchange and Treasury markets. Morningstar is one of the largest independent sources of fund, equity, and credit data and research in the world, and our advocacy for investors interests is the foundation of our company.The Role:As a Data Scientist, you will be a leading contributor in the implementation of Artificial Intelligence (AI) within Data Collections software applications, APIs, and other data products. This role requires significant interaction with both upstream and downstream stakeholders across Technology, Data, Products, Sales/Service, and Research.The Data Scientist will transition approved Data Collections AI products from a prototype phase to a scalable and consumable service. Often, these services must be integrated into Morningstars platform of financial products, so that our clients can use these software tools in the investment decision-making process.We are looking for an individual who possesses strong technical development skills, an ability to follow analyst requirements and technical specifications for robust code, and a passion for investment research.This position reports to the Tech Manager of the Data Collections AI team.This position is based in our Chicago office. We follow a hybrid policy of 3 days onsite and 2 days remote work. Candidates must be currently authorized to work Permanently in the United States - this position does not sponsor H-1B Visa.Responsibilities:Automate manual data collection processes by applying cutting-edge solutions to tackle NLP problems, e.g., text classification, NER tasks.Collaborate with upstream data analysts to clarify business needs, define project scope, design ML/AI solutions, and iteratively improve workflows and data storage practicesImplement ML/AI solutions from start to finish and collaborate with peer engineering teams for model deploymentDesign innovative ways to improve automation rates for data collectionResearch on latest technologies and propose new solutions to existing problemsParticipate in team brainstorming sessions, provide guidance to MLDAs (machine learning data analysts), and contribute to the codebaseIntroduce and follow good development practices, innovative frameworks and technology solutionsFollow best practices like estimation, planning, reporting and improvement brought to processes in daily workRequirements:No minimal industrial experience is required, if you have a Ph.D. degree in engineering, computer science, statistics or related fieldMust demonstrate ML/AI knowledge and skills through research and/or side-projects in NLP related fields, if you have no prior industrial experience Must have 2+ years of industrial experience in a data science role featuring NLP tasks, if you have a masters degree or belowFluent with Python and related packages like NumPy, pandas, scikit-learn, NLTK, PyTorch, TensorFlow, etc.Sound knowledge of common ML/AI algorithms (e.g., linear/logistic regression, random forest, gradient boosting) and Deep Learning algorithms in particular (e.g., transformers, BERT, open-source LLMs)Experience with SQLGreat communication and presentation skillsAble to work independently and being proactiveExperience with generative AI is preferredExperience with finetuning LLMs is preferredExperience with DevOps tools (e.g. Sagemaker, Git, Jenkins) is desirableExperience developing and deploying solutions using services in the Amazon AWS ecosystem (Lambda, Sagemaker, EC2, RDS, EMR)is desirableIntermediate knowledge of statistical methods is desirableFamiliarity with common data cleaning and munging techniquesFamiliarity with data visualizationFamiliarity with statistical methods, e.g., linear/logistic regression, optimizationFamiliarity with mutual fund, fixed income, and equity data is a plusCompensation and BenefitsAt Morningstar we believe people are at their best when they are at their healthiest. Thats why we champion your wellness through a wide-range of programs that support all stages of your personal and professional life. Here are some examples of the offerings we provide:Financial Health75% 401k match up to 7%Stock Ownership PotentialCompany provided life insurance - 1x salary + commissionPhysical HealthComprehensive health benefits (medical/dental/vision) including potential premium discounts and company-provided HSA contributions (up to $500-$2,000 annually) for specific plansand coveragesAdditional medical Wellness Incentives - up to $300-$600 annualCompany-provided long- and short-term disabilityinsuranceEmotional HealthTrust-Based Time Off6-week Paid Sabbatical Program6-Week Paid Family Caregiving LeaveCompetitive 8-24 Week Paid Parental Bonding LeaveAdoption AssistanceLeadership Coaching & Formal MentorshipOpportunitiesAnnual Education StipendTuition ReimbursementSocial HealthCharitable Matching Gifts programDollars for Doers volunteer programPaid volunteering days15+ Employee Resource & Affinity GroupsBase Salary Compensation Range$79,091.00 - 134,455.00 USD AnnualTotal Cash Compensation Range$87,000.00 - 147,900.00 USD AnnualMorningstars hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. While some positions are available as fully remote, weve found that were at our best when were purposely together on a regular basis, typically three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, youll have tools and resources to engage meaningfully with your global colleagues.001_MstarInc Morningstar Inc. Legal Entity #J-18808-Ljbffr