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Full Time Machine Learning Finance Jobs in Magnolia, NJ

Soni Resources

Data Scientist

Conshohocken, PA · On-site +1

$175K/yr

Background in insurance, financial services, or other highly regulated industries. * Experience building production-grade machine learning applications. * Master's or PhD in Data Science, Statistics ...

Slalom Consulting

General Information

Philadelphia, PA · On-site

$60.50 - $78.75/hr

Remote / Hybrid (Client-Facing Consulting Engagement) Employment Type: Full-Time Consultant ... Own the end-to-end machine learning production lifecycle, including data ingestion, feature ...

Vangard, Inc.

Senior AI Scientist

Philadelphia, PA

Strong experience utilizing statistical and machine learning methods required. Experience with ... To work for the long-term financial wellbeing of our clients. To lead through product and services ...

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All JobsMachine Learning Finance JobsFull Time Machine Learning Finance JobsFull Time Machine Learning Finance Jobs in Magnolia, NJ

Full Time Machine Learning Finance information

See Magnolia, NJ salary details

$25.6K

$94.7K

$138.6K

How much do full time machine learning finance jobs pay per year?

As of Aug 8, 2026, the average yearly pay for full time machine learning finance in Magnolia, NJ is $94,749.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,700.00 and $111,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a full time machine learning finance professional?

To thrive as a Full Time Machine Learning Finance professional, you need a solid background in quantitative analysis, statistics, computer science, and finance, usually supported by a relevant degree. Proficiency with programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with financial data systems are essential. Strong problem-solving abilities, attention to detail, and effective communication skills help you stand out in this field. These skills ensure the successful development and deployment of data-driven financial models that support better decision-making and risk management.

What is a full time machine learning finance professional?

A Full Time Machine Learning Finance job involves applying machine learning techniques and algorithms to financial data and problems. Professionals in this role develop predictive models for tasks such as risk assessment, trading strategies, fraud detection, and portfolio optimization. They work closely with financial analysts and data scientists to create solutions that can automate processes, improve decision-making, and identify patterns in large datasets. The role typically requires strong knowledge of both finance and advanced machine learning methods, as well as programming and data analysis skills.

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

AspectFull Time Machine Learning FinanceFull Time Data Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of finance and machine learning certificationsDegree in Statistics, Computer Science, or related fields; data analysis and programming skills
Work EnvironmentFinancial institutions, hedge funds, banks, fintech companiesTech companies, consulting firms, finance, healthcare, retail
Industry UsageFinance-specific applications like risk modeling, algorithmic tradingBroad industry applications including marketing, healthcare, finance

Full Time Machine Learning Finance roles focus on applying machine learning techniques specifically to financial data and problems within financial institutions. In contrast, Full Time Data Scientist positions have a broader scope across various industries, utilizing data analysis and modeling skills to solve diverse business challenges. While both roles require strong technical skills, the finance-specific role emphasizes financial knowledge and applications.

What are some common challenges faced by machine learning professionals working in the finance sector?

Machine learning professionals in finance often encounter challenges such as dealing with sensitive and highly regulated data, ensuring model transparency and explainability for compliance purposes, and adapting to rapidly changing market conditions. Additionally, integrating machine learning models with existing financial systems and collaborating closely with domain experts, such as quantitative analysts and risk managers, are key parts of the role. Staying updated on both technological advancements and regulatory changes is also essential for success in this dynamic environment.
Full Time Machine Learning Finance jobs near you
Infographic showing various Full Time Machine Learning Finance job openings in Magnolia, NJ as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $94,749 per year, or $45.6 per hour.

Machine Learning Internship - PhD: 2027

Susquehanna International Group, LLP

Philadelphia, PA • On-site

Full-time, Internship

Re-posted 2 days ago

Job description

Overview
Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.
As a Machine Learning Intern at Susquehanna, you'll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You'll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna's research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.
What You Can Expect
  • Conduct research and develop ML models to identify patterns in noisy, non-stationary data
  • Work side-by-side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging the gap between cutting-edge ML research and practical implementation
  • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
  • Design and run experiments using the latest ML tools and frameworks
  • One-on-one mentorship from experienced researchers and technologists
  • Participate in a comprehensive education program with deep dives into Susquehanna's ML, quant, and trading practices
  • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior
  • Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk-aware decision making

What we're looking for
  • Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field
  • Proven experience applying machine learning techniques in a professional or academic setting
  • Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR
  • Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow
  • Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment

Why Join Us?
  • Work with a world-class team of researchers and technologists
  • Access to unparalleled financial data and computing resources
  • Opportunity to make a direct impact on trading performance
  • Collaborative, intellectually stimulating environment with global reach

About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

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