Machine Learning Engineer

Posted 9 Days Ago
Chicago, IL
Hybrid
79K-148K Annually
Senior level
Enterprise Web • Fintech • Financial Services
The Role
The Machine Learning Engineer will lead ML function, develop data pipelines, refine models, analyze data, and present insights to stakeholders.
Summary Generated by Built In

About the Role
We're looking for a seasoned Machine Learning Engineer to lead the Machine Learning function within the Marketing Intelligence Team at Morningstar. This role will play a critical role by setting the requirements for the ML models, building the data pipelines and flows to power the model, as well as output model data that can be visualized and shared to business leaders. You will have deep technical data engineering skills and vision to build the machine learning road map. You will ensure models align to business goals, and are responsible for refining methodologies, iterating on models, and fine-tuning the model output. You will share out model findings to business stakeholders and tune and monitor models. You will evangelize model findings and feature engineering insights to marketing stakeholders and facilitate opportunities for stakeholders to use model output to deliver stronger business outcomes.
To foster continuous collaboration, we follow a hybrid policy of a minimum of 3 days onsite in our Chicago office.
Responsibilities

  • Build, fine-tune, and implement machine learning models to answer challenging business questions
  • Ensure machine learning production pipelines are scalable, repeatable, and cloud agnostic
  • Apply current and emerging techniques in deep learning, AI, and other machine learning areas
  • Collect, clean, manage, analyze, and visualize large sets of data using multiple data platforms, tools, and techniques
  • Optimize and fine-tune ML models for performance and scalability. Analyze and interpret data to extract meaningful insights and improve ML models
  • Maintain a database of model outputs, which will be used by the rest of the Marketing Intelligence team
  • Integrate ML solutions into Marketing Intelligence workstreams
  • Document and present findings and solutions to leaders and stakeholders


Requirements

  • Master's degree preferred, ideally in statistics, finance, mathematics, engineering, analytics, or in a quantitative discipline
  • 7+ years proven experience building data science models and executing data engineering work
  • Extensive experience in machine learning and statistical techniques, including regression, classification, clustering, time series forecasting, text analytics, and causal inference, and scaling end to end solutions
  • Expertise in marketing analytics & experimentation, such as Marketing Mix Modeling (MMM), Attribution Modeling, Lead Score Propensity Modeling
  • Proficiency in Python, R, and SQL, with strong scripting capabilities to process and transform data for modeling
  • Strong background in big data processing and engineering using Apache Spark, PySpark, and Airflow, with experience in data lakes and warehousing solutions (Snowflake, Databricks, Redshift, BigQuery)
  • Experience with MLOps and cloud platforms (AWS SageMaker, Bedrock, Google Vertex AI, Azure ML), with a track record of automating machine learning pipelines and building end-to-end ML products
  • Hands-on experience with machine learning libraries, including Scikit-learn, Pandas, NumPy, Matplotlib, SciPy, Seaborn, XGBoost
  • Hands-on experience with deep learning frameworks (TensorFlow, PyTorch)
  • Outstanding analytical and problem-solving skills with technical knowledge of setting requirements, working with complex data, and leveraging data stored across multiple data environments
  • The ability to solution alongside team members and thrive in a collaborative environment, and convey complex concepts in a clear and concise manner


Compensation and Benefits
At Morningstar we believe people are at their best when they are at their healthiest. That's 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 Health
    • 75% 401k match up to 7%
    • Stock Ownership Potential
    • Company provided life insurance - 1x salary + commission
  • Physical Health
    • Comprehensive health benefits (medical/dental/vision) including potential premium discounts and company-provided HSA contributions (up to $500-$2,000 annually) for specific plans and coverages
    • Additional medical Wellness Incentives - up to $300-$600 annual
    • Company-provided long- and short-term disability insurance
  • Emotional Health
    • Trust-Based Time Off
    • 6-week Paid Sabbatical Program
    • 6-Week Paid Family Caregiving Leave
    • Competitive 8-24 Week Paid Parental Bonding Leave
    • Adoption Assistance
    • Leadership Coaching & Formal Mentorship Opportunities
    • Annual Education Stipend
    • Tuition Reimbursement
  • Social Health
    • Charitable Matching Gifts program
    • Dollars for Doers volunteer program
    • Paid volunteering days
    • 15+ Employee Resource & Affinity Groups


Base Salary Compensation Range
$79,091.00 - 134,455.00 USD Annual
Total Cash Compensation Range
$87,000.00 - 147,900.00 USD Annual
Morningstar's hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. While some positions are available as fully remote, we've found that we're at our best when we're 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, you'll have tools and resources to engage meaningfully with your global colleagues.
001_MstarInc Morningstar Inc. Legal Entity

Top Skills

Airflow
Spark
Aws Sagemaker
Azure Ml
Bedrock
BigQuery
Databricks
Google Vertex Ai
Matplotlib
Numpy
Pandas
Pyspark
Python
PyTorch
R
Redshift
Scikit-Learn
Scipy
Seaborn
Snowflake
SQL
TensorFlow
Xgboost

What the Team is Saying

Raaghavendar
Saurabh
Anna
Wendell
Jeff
Upasna
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The Company
HQ: Chicago, IL
12,700 Employees
Hybrid Workplace
Year Founded: 1984

What We Do

At Morningstar, we believe in building great products in-house in a highly collaborative, agile environment where we focus on technical excellence, the user experience, and continuous improvement. Our technologists represent a range of skills and experience levels, but they all view their work as a craft and push technology’s boundaries.

Why Work With Us

Imagining big things is in our blood -- it's transformed us from a company with just a few employees in 1984 to a leading independent investment research company with a worldwide presence today. As of April 2020, we acquired Sustainalytics to drive long-term meaningful outcomes for investors in the ESG space. Join us on this exciting journey!

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Morningstar Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: 3 days a week
HQGlobal Headquarters
Santiago Province
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London, GB
Madrid, ES
Mexico City, Mexico City
Milano, IT
Navi Mumbai, Maharashtra
New York, NY
Oakland, MD
Oslo, NO
Paris, FR
São Paulo, São Paulo
PitchBook US Headquarters
Stockholm, SE
Tokyo, JP
Toronto, ON
Toronto, Ontario
Zürich, CH
Learn more

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