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Lead Data Scientist
ParetoHealth, a healthcare benefits captive, is hiring a Lead Data Scientist to independently own end-to-end predictive underwriting and pricing workstreams — from problem framing and feature engineering through model deployment, monitoring, and business-impact measurement. Core stack: Python, SQL, scikit-learn/XGBoost, PySpark, and AWS-based MLOps.
Data Scientist
Data Scientist at digital marketing agency Monks in Mexico City, building predictive models, segmentation, churn, and recommendation solutions for client projects. Day-to-day spans data mining, ML model development and deployment using Python/R, cloud platforms, SQL databases, and BI tools, working closely with analytics and account teams.
Senior Quantitative Developer
Senior Quantitative Developer on Man Systematic's front-office engineering team in Boston: builds trading signals, dataset pipelines, portfolio optimization tools and research platform features alongside quant researchers. Stack is Python (Pandas/NumPy/SciPy) with Java for high-throughput systems, MongoDB/MS SQL, and a Linux toolchain (Airflow, Kafka, Docker).
Staff Software Engineer, Machine Learning
Builds and ships machine-learning models and optimization algorithms (budget pacing, automated bidding) for DoorDash's ads platform and catalog/product knowledge graph, owning the end-to-end ML lifecycle from training through deployment, experimentation, and monitoring. Hybrid role using PyTorch, PySpark, and Snowflake.
AI Engineer
AI Engineer at Ford in Dearborn, MI (on-site 4 days/week) building analytical, machine learning, and AI solutions to improve customer experience, revenue, and efficiency. Works the full ML lifecycle — preprocessing, feature engineering, training, evaluation, deployment — using Python (TensorFlow, PyTorch, scikit-learn), GenAI, and cloud/AI platforms.
Applied AI/ML Engineer
Oddball is hiring an Applied AI/ML Engineer to design, build, and deploy production ML and GenAI features (LLM workflows, RAG, classification, NLP) for its federal-space software work. Day to day spans prototyping, data pipelines, model evaluation, and integrating models into services, using Python, PyTorch/TensorFlow, and SQL/Spark.
Freelance Data Science Engineer (Python & SQL)
Freelance, project-based role at Mindrift: design and verify original computational data science problems (Python with pandas/numpy/scikit-learn, plus SQL) that simulate real-world business workflows to support GenAI model training. Estimated 10-20 hours/week during active project phases, paid up to $55/hour.
[NA] Data Scientist Senior Dataiku – Banque – GCP – GenAI
Senior data scientist embedded in a large banking group's Data & AI department, building generative and predictive AI use cases: designing and industrializing workflows in Dataiku, preparing data, training and deploying models, and integrating with GCP (BigQuery, GCS, IAM).
Product Engineer (Advance Data Analytics), Heterogeneous Integration Group...
Product Engineer in Micron's HBM Product Engineering Advanced Data Analytics team, driving semiconductor yield and quality improvement through statistical analysis, machine learning, and AI models, while building data infrastructure pipelines and collaborating with cross-functional teams. Onsite in Singapore with travel to Taiwan.
Remote Machine Learning Engineer - Big Data Analytics
Fully remote machine learning engineer for a data analytics firm, owning the end-to-end ML lifecycle — building data pipelines, training and deploying models on big data tech like Spark/Hadoop — using Python/Scala, cloud ML services, and MLOps practices.
Binance Accelerator Program - Data Scientist (User Growth)
Data science intern in Binance's Accelerator Program (Singapore) building user-growth algorithms for the world's largest crypto exchange: user segmentation, LTV/churn prediction models, incentive strategies, and A/B tests. Core stack is Python (NumPy, Pandas, Scikit-learn) plus SQL and classical ML models.
PhD Machine Learning Engineer, Intern
Summer 2027 PhD machine learning engineering internship at Stripe (San Francisco, NYC, Seattle) within Applied ML, Data Science, Risk, and Payments. Interns design, train, and deploy production-scale ML systems — e.g., fraud detection, Stripe Assistant, and the Stripe Foundation Model — using Python, Scala, Spark, and common ML libraries.
Master's Machine Learning Engineer, Intern
A summer 2027 Master's-level machine learning internship at Stripe (SF, NYC, or Seattle), where interns design, train, and deploy production-scale ML systems across Applied ML, Risk, and Payments — including fraud detection, the Stripe Assistant, and the Stripe Foundation Model. Core technologies include Python, Scala, Spark, Pandas, NumPy, and Scikit-learn.
AI Engineer
AI Engineer at NTT DATA's Romania Excellence Centre in Bucharest, building LLM-powered multi-agent systems for a digital banking client. Day-to-day: designing agentic workflows, orchestration, RAG pipelines, and evaluation suites with Python, Google ADK/LangGraph, vector databases, and cloud platforms.
Engenheiro de Machine Learning
Machine Learning Engineer working on-site in Curitiba for LUZA Group, building ML solutions for Grupo Senff: developing, training, and deploying predictive models, data pipelines, and MLOps practices (versioning, monitoring, retraining) using Python, Scikit-learn/Pandas/NumPy, SQL, Docker, Git/CI-CD, and REST APIs.
Cientista de Dados
On-site Data Scientist in Curitiba supporting Grupo Senff's strategic and operational decisions through exploratory analysis, statistical and predictive modeling, SQL data extraction, and BI dashboards. Core stack: Python (Pandas, Scikit-learn, Statsmodels), SQL, and Power BI/Tableau; payments, credit and fraud-prevention experience is a plus.
Data Scientist (CLEARANCE REQUIRED)
Senior Data Scientist at STR develops advanced analytics and machine learning algorithms for national security applications, including signals exploitation and predictive tracking, using Python/C++ and data science tools.