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Hedge Fund Machine Learning Jobs in Minnesota (NOW HIRING)

University of Minnesota

Gardener

Minneapolis, MN

$27.70 - $31.46/hr

... machinery including mowers, aerators, skid steer loaders (with attachments), weed whips, hedge ... Continuous learning opportunities through professional training and degree-seeking programs ...

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Hedge Fund Machine Learning information

What are the typical projects or challenges a hedge fund machine learning professional may encounter?

As a Hedge Fund Machine Learning professional, you may work on projects involving the development of predictive models for market movements, portfolio optimization, anomaly detection, or automated trading strategies. Common challenges include sourcing high-quality financial data, managing noisy or incomplete information, and ensuring that models remain robust in dynamic market conditions. Additionally, you will often collaborate with portfolio managers, data engineers, and other quant researchers to translate model insights into actionable investment strategies. Overcoming these challenges requires both technical expertise and adaptability, offering significant opportunities for career growth and impact within the fund.

What are the key skills and qualifications needed to thrive in hedge fund machine learning?

To thrive in a Hedge Fund Machine Learning role, you need a strong background in quantitative analysis, statistics, programming (often in Python or R), and machine learning, typically supported by a degree in mathematics, computer science, or a related field. Proficiency with data analysis libraries (like pandas, NumPy), machine learning frameworks (such as TensorFlow or scikit-learn), and experience with financial data sets or platforms is highly valuable. Effective communication, collaboration, and a strong problem-solving mindset are crucial soft skills in this role. These competencies are essential to designing and implementing robust trading models, navigating complex data, and working efficiently in a fast-paced, team-driven environment.

What is a hedge fund machine learning?

A Hedge Fund Machine Learning job involves applying data science, artificial intelligence, and quantitative modeling techniques to improve trading strategies, risk management, and portfolio optimization. Professionals in this role develop and implement machine learning algorithms to analyze financial data, identify patterns, and generate predictive models for market behavior. They work closely with portfolio managers, traders, and quantitative researchers to enhance decision-making and generate alpha. Strong programming skills, expertise in statistics, and knowledge of financial markets are essential for success in this field.

What are popular job titles related to Hedge Fund Machine Learning jobs in Minnesota? For Hedge Fund Machine Learning jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Hedge Fund Machine Learning jobs in Minnesota look for? The top searched job categories for Hedge Fund Machine Learning jobs in Minnesota are:
What cities in Minnesota are hiring for Hedge Fund Machine Learning jobs? Cities in Minnesota with the most Hedge Fund Machine Learning job openings:
Hedge Fund Machine Learning jobs near you
Infographic showing various Hedge Fund Machine Learning job openings in Minnesota as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, and 2% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution.

AI Ops Engineer

Tata Consultancy Service Limited

Eden Prairie, MN • On-site

$100K - $120K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 20 days ago

Job description

Role Summary
Builds, trains and tunes machine learning models. Translates data science experiments into scalable, production-ready ML solutions.
Key Responsibilities
Translate data science prototypes into production-grade ML services and pipelines.
- Build training and inference code with reproducibility, versioning, and automated testing.
- Implement scalable model serving (online/offline), batching, and latency/throughput optimization.
- Integrate model lifecycle tooling (tracking, registry, deployment automation, monitoring).
- Collaborate with Data Engineering on feature pipelines and data contracts.
- Own production health: drift detection, performance regression, rollback strategies, and incident response.
Required Qualifications
- 5+ years software engineering with 2+ years shipping ML models to production.
- Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).
- Experience with containers and orchestration (Docker/Kubernetes) and API development.
- Understanding of ML system design (data leakage, training-serving skew, drift).
- CI/CD and DevOps practices applied to ML workloads (MLOps).
Experience with CI/CD and DevOps practices applied to ML (MLOps)
Salary Range: $100,000- $120,000 a year
TCS Employee Benefits Summary:
Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement.
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
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