Morningstar
Lead Machine Learning Engineer
Morningstar - Chicago, Illinois, United States, 60290
Work at Morningstar
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Overview
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Lead Machine Learning Engineer
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Morningstar 2 days ago Be among the first 25 applicants Join to apply for the
Lead Machine Learning Engineer
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Morningstar Get AI-powered advice on this job and more exclusive features. 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. 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
$96,326.00 - 163,761.00 USD Annual
Total Cash Compensation Range
$110,775.00 - 188,325.00 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 Seniority level
Seniority level Mid-Senior level Employment type
Employment type Full-time Job function
Job function Information Technology, Engineering, and Finance Referrals increase your chances of interviewing at Morningstar by 2x Sign in to set job alerts for “Machine Learning Engineer” roles.
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Lead Machine Learning Engineer
role at
Morningstar 2 days ago Be among the first 25 applicants Join to apply for the
Lead Machine Learning Engineer
role at
Morningstar Get AI-powered advice on this job and more exclusive features. 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. 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
$96,326.00 - 163,761.00 USD Annual
Total Cash Compensation Range
$110,775.00 - 188,325.00 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 Seniority level
Seniority level Mid-Senior level Employment type
Employment type Full-time Job function
Job function Information Technology, Engineering, and Finance Referrals increase your chances of interviewing at Morningstar by 2x Sign in to set job alerts for “Machine Learning Engineer” roles.
Chicago, IL $110,000.00-$130,000.00 5 days ago Entry Level Software Engineer, application via RippleMatch
Machine Learning Scientist, Digital Pathology
Chicago, IL $105,000.00-$140,000.00 2 weeks ago Chicago, IL $105,000.00-$140,000.00 2 weeks ago Predoctoral Scholar - Machine Learning Data Scientist
Deerfield, IL $98,600.00-$157,500.00 6 days ago Chicago, IL $184,000.00-$276,100.00 1 week ago We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr