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Manager Machine Learning Finance Jobs in Illinois

Coinflow

Machine Learning Lead

Chicago, IL · On-site

$225K - $275K/yr

... global financial infrastructure with stablecoins, AI-driven fraud prevention, and instant ... Experience developing, managing, and scaling MLOps pipelines and monitoring systems (retraining ...

Unchain Data

Machine Learning Lead

Chicago, IL · On-site

$225 - $275/hr

... global financial infrastructure with stablecoins, AI-driven fraud prevention, and instant ... Experience developing, managing, and scaling MLOps pipelines and monitoring systems (retraining ...

New

SOLANA FOUNDATION

Machine Learning Lead

Chicago, IL · On-site

$175 - $235/hr

... global financial infrastructure with stablecoins, AI-driven fraud prevention, and instant ... Experience developing, managing, and scaling MLOps pipelines and monitoring systems (retraining ...

New

Referrals Only

Lead Machine Learning Engineer

Chicago, IL · On-site

$105K - $139K/yr

Lead Machine Learning Engineers at Thoughtworks use modern architectures to develop end-to-end ... Azure, AWS, GCP and/or Databricks and associated ML managed services. Professional Skills * You ...

Socket.dev

Machine Learning Software Engineer 1

Chicago, IL · On-site

$62 - $100/hr

You won't be on your own on day one, but you will need the capacity to manage your time between ... Working within a finance and accounting firm, recognize and appropriately elevate risks and support ...

New

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

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Manager Machine Learning Finance information

What does a manager of machine learning in finance do?

A Manager of Machine Learning in Finance oversees teams that develop and implement machine learning models to solve financial problems, such as risk assessment, fraud detection, and algorithmic trading. They coordinate with data scientists, engineers, and business stakeholders to ensure models meet regulatory standards and align with company goals. Additionally, they are responsible for project management, mentoring team members, and staying updated with advancements in both finance and artificial intelligence.

How does a manager of machine learning in finance typically collaborate with cross-functional teams?

A Manager of Machine Learning in Finance often works closely with data scientists, software engineers, financial analysts, and business stakeholders. They are responsible for translating business problems into machine learning solutions and ensuring models meet both technical and regulatory requirements. Regular meetings and clear communication are essential, as the manager must align team efforts with organizational goals, facilitate knowledge sharing, and integrate model outputs into financial decision-making processes. Collaboration also involves coordinating with IT for data infrastructure and with compliance teams to uphold data privacy standards.

What are the key skills and qualifications needed to thrive as a manager of machine learning in finance, and why are they important?

To thrive as a Manager of Machine Learning in Finance, you need strong expertise in machine learning, statistics, and financial analysis, typically supported by a relevant advanced degree and experience in both data science and finance. Familiarity with programming languages like Python or R, cloud platforms, and machine learning frameworks such as TensorFlow or Scikit-learn is essential, along with knowledge of regulatory compliance systems. Exceptional leadership, strategic thinking, and communication skills set top candidates apart by enabling effective team management and cross-functional collaboration. These skills and qualities are crucial to drive innovative solutions, ensure regulatory adherence, and deliver business value in a complex financial environment.

What is the difference between Manager Machine Learning Finance vs Data Scientist Finance?

AspectManager Machine Learning FinanceData Scientist Finance
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or Finance; certifications in machine learning or data analysisBachelor's or Master's in Data Science, Statistics, or related fields; often includes certifications in data analysis or programming
Work EnvironmentLeads teams, manages projects, collaborates with stakeholders in financeAnalyzes data, develops models, supports decision-making in finance teams
Employer & Industry UsageFinancial institutions, hedge funds, investment firmsFinancial firms, banks, fintech companies

The Manager Machine Learning Finance oversees teams and projects applying machine learning to finance problems, focusing on leadership and strategy. In contrast, Data Scientists in finance primarily analyze data and develop models to support financial decisions. Both roles require strong technical skills, but the manager role emphasizes team management and project oversight.

Can manager machine learning finance be used in finance?

A Manager of Machine Learning in Finance oversees the development and implementation of machine learning models to improve financial analysis, risk management, and trading strategies. This role involves skills in data science, programming, and finance, and is used to enhance decision-making processes and automate tasks within financial institutions.

What are the most commonly searched types of Machine Learning Finance jobs in Illinois?

The most popular types of Machine Learning Finance jobs in Illinois are:

What cities in Illinois are hiring for Manager Machine Learning Finance jobs?

Cities in Illinois with the most Manager Machine Learning Finance job openings:

Manager Machine Learning Finance jobs near you

Machine Learning Lead

Coinflow

Chicago, IL • On-site

$225K - $275K/yr

Full-time

Medical, Retirement

Re-posted 25 days ago

Job description

About Coinflow
Coinflow is the next-generation payment service provider revolutionizing global financial infrastructure with stablecoins, AI-driven fraud prevention, and instant settlement. Coinflow enables businesses to grow faster with instant settlement, fraud & chargeback indemnity, global pay-ins, multi-currency FX, and unified payouts. Founded in 2023, the company serves marketplaces, fintechs, remittance providers, gaming platforms, and ecommerce merchants worldwide.
Since our seed round in 2024, we've achieved 23x revenue growth and scaled to multi-billion-dollar annual transaction volume. In response to this growth, Coinflow announced a $25M Series A in October 2025-led by Pantera Capital, CMT Digital, Coinbase Ventures, Jump Crypto, and Reciprocal Ventures-accelerating our mission to power the world's fastest-moving businesses with innovative, reliable global payments.
Coinflow is proudly headquartered in Chicago, IL. Learn more at coinflow.cash.
Role Overview:
Coinflow is seeking a Machine Learning Lead to own the fraud and risk intelligence layer at the core of our platform.
This is a founding ML role. You'll lead our first dedicated ML team, building capabilities that combine our first-party transaction data with partner signals to optimize approval rates across payment methods and geographies, sharpen risk decisioning during merchant underwriting, and improve fraud detection across global payment methods. That means digging into large-scale transaction and behavioral data, shipping production fraud models, defining what good looks like, and continuously raising the bar on detection and precision as our volume and merchant base scale.
The ideal candidate has hands-on experience building fraud models on the acquiring side of payments and working alongside external fraud vendors to tackle card-present or card-not-present fraud, authorization decisioning, chargeback reduction, and related risk systems.
Key Responsibilities
  • Strengthen Coinflow's fraud detection and risk decisioning capabilities - feature engineering, model development, and production deployment
  • Own the full model lifecycle: experimentation, evaluation, monitoring, and iteration
  • Define and track core fraud and risk metrics - detection rate, false positive rate, chargeback rate, dispute win rate - and continuously improve them
  • Explore transaction and behavioral data to surface new fraud signals and emerging attack patterns
  • Partner with Engineering, Product, and Operations to embed fraud intelligence directly into payment flows and internal tooling
  • Integrate and orchestrate external fraud/risk partners, getting maximum value from their tooling
  • Establish the foundation for ML and data practices across the company
  • Help shape Coinflow's long-term fraud, risk, and ML roadmap
Required Qualifications
  • 5+ years in machine learning, applied data science, or production ML roles
  • Demonstrated experience building fraud models in payments, with direct exposure to the acquiring side - acquirer, PSP, or payment facilitator
  • Proven track record taking ML projects from proof-of-concept to fully deployed, productionized systems
  • Deep familiarity with acquiring-side fraud dynamics: authorization fraud, card-not-present fraud, friendly fraud, chargeback patterns, and merchant risk
  • Strong foundation in ML, statistics, and feature engineering on high-volume financial data
  • Comfortable owning ambiguous problems end-to-end and creating structure where none exists
  • Strong collaborator across Engineering, Product, and Ops
Preferred Qualifications
  • Experience at an acquirer, ISO, PayFac, or payments infrastructure company
  • Experience developing, managing, and scaling MLOps pipelines and monitoring systems (retraining schedules, real-time performance metrics)
  • Experience scoping cloud compute requirements for scalable ML workloads
  • Familiarity with card network rules, dispute/chargeback workflows, and fraud liability frameworks
  • Experience as an early or sole ML hire at a startup
  • Exposure to real-time or near-real-time fraud scoring systems
  • Experience with stablecoin, crypto, or alternative payment rails

What We Offer:
  • Competitive compensation including base salary, performance bonus, and meaningful ownership
  • Opportunity to build the fraud and risk intelligence layer of a rapidly scaling fintech company
  • Collaborative and innovative work environment with world-class investors
  • Direct impact on core risk infrastructure and company trajectory during a hyper growth phase

The base salary range for this role is $225,000 - $275,000 USD. The actual base salary offered depends on a variety of factors, including but not limited to experience, education, skills, qualifications and business needs.
In addition, the employee who fills this role will be eligible for an equity grant, allowing you to share in the long-term success of the company. You will also have access to a wide array of benefits, including health and wellness benefits, 401(k) savings plan, and flexible time off.
Join the team rewriting how money moves worldwide-and become a driving force in the $194 trillion cross-border payments market.

Apply