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Manager Machine Learning Finance Jobs in Homestead, FL

Opendoor

Machine Learning Engineer

Miami, FL · On-site

We don't have project managers, we don't have scrum. We do reviews, proposals, demos, and trust. What We're Looking For You ship. You pick the boring solution when boring is right and the novel one ...

Deloitte

Finance Analytics & AI Senior Consultant

Miami, FL · On-site

$111K/yr

Experience deploying machine learning or generative and agentic AI solutions into production ... Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment * Strong ...

Deloitte

Finance Analytics & AI Manager

Miami, FL · On-site

One or more certifications in artificial intelligence, machine learning, Amazon Web Services ... Work you'll do As a Finance Analytics & AI Manager on the Finance Transformation team, you'll work ...

Deloitte

Finance Analytics & AI Manager

Miami, FL · On-site

One or more certifications in artificial intelligence, machine learning, Amazon Web Services ... Work you'll do As a Finance Analytics & AI Manager on the Finance Transformation team, you'll work ...

Anson McCade

AI Researcher / AI Engineer

Miami, FL · On-site

$250K/yr

... machine learning to solve some of the most complex challenges in global financial markets. With a long-standing reputation for innovation and technical excellence, the firm continues to invest ...

The Voleon Group

Business Strategy Manager

Miami, FL · On-site

$125K - $150K/yr

... machine learning techniques to real-world problems in finance. For nearly two decades, we have led ... We have become a multibillion-dollar asset manager, and we have ambitious goals for the future.

Deloitte

Oracle Gen AI Manager

Miami, FL · On-site

Today's chief financial officers (CFOs) and supply chain executives are being asked to improve ... machine learning initiatives * Identify high-value AI use cases and guide teams on prompt ...

Deloitte

Financial Risk Manager

Miami, FL · On-site

... machine learning, and other digital strategies * Manage the development of client deliverables or ... Required Qualifications * Bachelor's degree in Finance, Economics, Business, Statistics ...

Pwc

CTIO AI Engineering Manager

Miami, FL

$73K - $244K/yr

Industry/Sector Not Applicable Specialism IFS - Information Technology (IT) Management Level ... Those in data science and machine learning engineering at PwC will focus on leveraging advanced ...

Accenture

AI/ML Computational Science Specialist

Miami, FL · On-site

$70K - $205K/yr

Develop system specifications, create test plans, and conduct project and issue management for the assigned scope of work. * Design/Build solutions using AI services and machine learning models to ...

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All JobsMachine Learning Finance JobsManager Machine Learning Finance JobsManager Machine Learning Finance Jobs in Homestead, FL

Manager Machine Learning Finance information

See Homestead, FL salary details

$38.6K

$114.2K

$155.3K

How much do manager machine learning finance jobs pay per year?

As of Jul 28, 2026, the average yearly pay for manager machine learning finance in Homestead, FL is $114,216.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,800.00 and $154,300.00 per year, depending on experience, location, and employer.

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.

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.

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.
Manager Machine Learning Finance jobs near you
Infographic showing various Manager Machine Learning Finance job openings in Homestead, FL as of June 2026, with employment types broken down into 64% Full Time, 33% Part Time, 1% Temporary, and 2% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $114,216 per year, or $54.9 per hour.
Machine Learning Engineer

Machine Learning Engineer

Opendoor

Miami, FL • On-site

Full-time

Posted 8 days ago

Job description

About Opendoor
At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It's how families put down roots, how neighborhoods strengthen, how the future gets built. We're building the modern system of homeownership giving people the freedom to buy and sell on their own terms. We've built an end-to-end online experience that has already helped thousands of people and we're just getting started.
About the Role - Senior and Above
You're interviewing for Opendoor's ML team which seeks to automate and refine every decision made in our product. We don't slot into silos; you'll build where you have the most impact and the most fun.
These are builder roles across the ML stack. Wherever you land, you'll be doing one of three things:
  • Building models in business-critical contexts like pricing, risk, repairs, and decision optimization. Leverage frontier techniques to extend our capabilities into the unstructured world of real estate.
  • Building the intelligent services that bring structured, precise decision-making into the highly unstructured world of real estate.
  • Building platforms that accelerate how fast our models learn. How fast we learn dictates how fast this company can grow.

You'll work directly with researchers, product, and operations to build the automation that scales in the real world. Our systems must be agile, accurate, and resilient in a heterogeneous space. We are growing fast and this work is at the core.
This isn't a role for everyone. We choose hard mode. We're process-light, high-trust, and we don't put artificial boundaries between you and the work. You'll be expected to understand how your piece connects to the product and communicate at that level. We don't have project managers, we don't have scrum. We do reviews, proposals, demos, and trust.
What We're Looking For
You ship. You pick the boring solution when boring is right and the novel one when it isn't. You know when "good enough and shipped today" beats "perfect next quarter."
You have high agency. You don't wait for permission or a perfectly scoped ticket. You see the problem, take ownership end-to-end, and pull in whoever you need. Lean teams, significant latitude, real accountability.
You run at unclear problems. The most valuable problems here don't come with a playbook - messy data, imperfect ground truth, markets that shift under you. Ambiguity is the job, not an obstacle to it.
You hold a high standard. You measure twice and cut once. You review code, raise the bar on everything around you, and treat the quality of our end-to-end judgment as your problem.
You think in first principles. You have opinions on architecture, distributed systems, ML lifecycle tradeoffs, and the constraints and tripwires of operating models in a high-stakes environment.
You default to AI. You've already integrated modern AI tools into your daily workflow. You use them to move faster, not as a crutch.
You communicate well. You write clear design docs, give useful code reviews, push back on bad ideas without making it personal, and can land a technical tradeoff with a non-technical stakeholder.
You believe in what we're building. Not hype, conviction. You see the opportunity in what we're doing and you want to be part of finishing it.
You have fun. We stay human when times are hard. The task is daunting, but we're all in it together.
What You'll Do
  • Build and train models that real customers and real money depend on - pricing, automation, and decision systems in production
  • Work side-by-side with researchers and analysts to turn prototypes into clean, testable, production-ready code and systems
  • Own model pipelines end-to-end: data ingestion, training, validation, versioning, deployment, and monitoring
  • Design, build, and evolve mission-critical services and APIs that connect to real-world, messy operations
  • Build the platform that accelerates the full ML lifecycle: agentic research, automated retraining, experimentation, deployment, monitoring
  • Proactively tackle real-world challenges like sparsity, data drift, and model decay in a volatile market
  • Use AI tools daily and help push them further than anyone else in the industry
  • Lead technical design reviews, mentor teammates, and raise the bar on everything around you

Qualifications
  • Senior-level or above: deep experience shipping and operating production ML systems, ML-adjacent services, or data/ML platforms
  • Strong fundamentals in Python; comfortable picking up new ones
  • Proficiency with statistics and ability to reason distributionally; has put it to work with real-world monitoring of ML systems
  • Expertise with the end-to-end ML lifecycle (training, evaluation, deployment, monitoring, and iteration) and associated tooling (e.g. MLflow, Airflow, Spark, Delta Lake)
  • Demonstrated ability to make and communicate design decisions and tradeoffs across stakeholders
  • Based in or willing to relocate to Miami, Toronto, or Seattle

Nice to Have
  • ML systems experience in business-critical domains: pricing, forecasting, logistics, marketplaces, risk
  • Streaming and event-driven systems (e.g. Kafka), gRPC, Redis, or workflow engines
  • Interest in real estate or other messy, high-stakes domains with imperfect data

Interview Process
We move fast. Typically:
  • Recruiter phone screen (15 min)
  • A 60 minute technical deep dive to understand a past problem or project you've worked on
  • Two 60 minute pairing-style technical reviews

We're not running these to see if you can finish a problem under pressure. We want to know what it's like to work with you. Before each interview you'll receive an email on what to expect.
Not a perfect fit on paper but clearly excellent? Apply anyway and tell us why in your cover letter. We value T-shaped people. If you have deep expertise in an adjacent area and a strong point of view on how it applies here, that's exactly who we want to talk to.
About Opendoor
At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It's how families put down roots, how neighborhoods strengthen, how the future gets built. We're building the modern system of homeownership, giving people the freedom to buy and sell on their own terms. We've built an end-to-end online experience that has already helped thousands of people - and we're just getting started.

Apply