Statistical machine learning jobs

Internship - Research Intern, Speech & Language Processing

Apple · Posted Nov 4, 2026

Open

Copenhagen, Capital Region, Denmark
On-site
Internship · Intern

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Internship - Research Intern, Speech & Language Processing

Apple · Posted Nov 4, 2026

Open

Copenhagen, Capital Region, Denmark
On-site
Internship · Intern

Apply with Referso

Quantitative Researcher - ML

Man Group · Posted Nov 4, 2026

Open

Shanghai, China

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Develop and improve AI-driven quantitative investment strategies in financial markets within the dedicated China research team.

Responsibilities

Develop and improve AI-driven quantitative investment strategies
Support all strategies from alpha generation through to trade execution and implementation
Design, build, and enhance strategies using cutting-edge machine learning and AI techniques
Leverage large language models, NLP, and alternative data pipelines to identify novel investment signals
Apply AI-powered data processing and feature engineering techniques to gather, clean, and structure complex datasets

Requirements

Advanced degree in Computer Science, Statistics, Mathematics, Finance/Economics or related quantitative field from a top-tier institution
Nice to have: Prior experience in the investment field

Skills

Large language models NLP Machine learning Deep learning Reinforcement learning

Senior Machine Learning Engineer

EvolutionIQ · Posted Nov 4, 2026

Open

Chicago, Illinois, United States
Senior
$180K–$225K per year
5+ years

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Lead end-to-end development of machine learning models and evaluations for auto casualty claims, driving product decisions and impact measurement.

Compensation

Salary range is: $180,000 - 225,000

Responsibilities

Build and ship statistical, ML, and hybrid LLM models on real claims data
Design evaluations and gold datasets with data labelers and subject matter experts
Run continuous evaluations as product changes
Measure impact through experiment design, baselines, and ROI analysis
Explain results to product, sales, and customers

Requirements

Degree in statistics, probability, or related field
Nice to have: causal inference
Nice to have: survival analysis
Nice to have: calibration methods
Nice to have: fine-tuning domain-specific models

Skills

Python SQL statistical machine learning LLM-based approaches RAG embeddings

Research Scientist/Engineer 4 - Biostatistics Department (temporary)

University of Washington · Posted Nov 3, 2026

Open

Seattle, Washington, United States
Hybrid
Temporary
$108K–$156K per year
4+ years

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Develop and deploy statistical machine learning and AI methods and software tools for analysis of diverse biomedical data

Compensation

Pay Range Minimum: $108,000.00 annual Pay Range Maximum: $156,000.00 annual

Responsibilities

Develop and deploy statistical machine learning and AI methods and software tools for analysis of diverse biomedical data
Lead and contribute to scientific investigations by biomedical scientists to analyze multi-modal biomedical data to discover new biomarkers and investigate mechanisms of complex diseases
Disseminate study findings through reports and presentations for progress reports and peer-review publications
Lead multidisciplinary projects by collaborating with team members, including other research scientists and graduate students
Provide technical guidance and project management expertise to junior team members and students

Requirements

Master’s degree in biostatistics, statistics, computer science, or a related field
Nice to have: Doctoral degree in biostatistics, statistics, computer science, or a related field
Nice to have: Experience working with diverse biomedical data

Skills

R Python

Internship - Research Intern, Speech & Language Processing

Internship - Research Intern, Speech & Language Processing

Responsibilities

Requirements

Skills

Quantitative Researcher - ML

Responsibilities

Requirements

Skills

Senior Machine Learning Engineer

Compensation

Responsibilities

Requirements

Skills

Research Scientist/Engineer 4 - Biostatistics Department (temporary)

Compensation

Responsibilities

Requirements

Skills

Benefits

Benefits