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Data Engineer bridging Azure pipeline architecture and ML forecasting model development for enterprise-scale workforce analytics, using Azure SQL, Databricks, Python, and Power BI.
Lead applied ML projects for industry clients, mentor junior staff, and translate academic research into practical solutions using Python, PyTorch, and related ML frameworks at an AI research institute in Edmonton.
Senior Consultant applying data science, AI, and analytics to healthcare and life sciences commercial challenges—building predictive models, supporting AI solutions, and delivering client-ready insights using Python, SQL, and ML techniques.
Onsite Software Developer building REST APIs and web applications with React, TypeScript, Node.js, and Next.js, plus AI/ML integrations (Agentic AI, RAG, LLMs) for a government/public sector client in Toronto or Peterborough.
Senior ML Engineer designing scalable AI platforms, defining governance frameworks, and leading cross-team ML strategy to deploy safe, high-impact models at Creai, a data-driven AI startup.
Customer Insights Analyst using SQL, Python/R, and BI tools to analyze customer behavior, build predictive models (churn, LTV, propensity), and deliver data-driven insights to marketing and brand teams at an international travel company.
Builds and maintains a real-time customer data platform (CDP) called Atlas, focusing on event streaming, identity resolution, and Snowflake/dbt pipelines to unify customer data for media/entertainment insights.
Developing and deploying production ML/DL models for time series forecasting and financial market prediction in a DeFi and algorithmic trading product team, using Python, PyTorch, and gradient boosting frameworks.
The Machine Learning Engineer will design, develop, and deploy scalable ML models for Capital Markets applications using Python, PySpark, and various ML frameworks. The role involves managing the full ML lifecycle, including pipeline development, model optimization, and production integration.
The Lead ML/AI Platform Engineer will own the end-to-end machine learning infrastructure, including training, model serving, and integration with Java microservices. The role focuses on driving the company's GenAI and agentic workflow strategy using AWS-based tools and open-source ML frameworks.
Deploy Fundamental's NEXUS Large Tabular Model into production for Houston-based Oil & Gas enterprise customers, performing end-to-end ML work including benchmarking against XGBoost/LightGBM, data engineering, feature engineering, and last-mile integration (VPC, on-prem, air-gapped).
Designs and deploys reinforcement learning models to personalize marketing campaigns for global brands using Python, TensorFlow, and SQL.
La Fundación para el Desarrollo y la Innovación Tecnológica ( Funditec ) es un centro de investigación aplicada sin ánimo de lucro que promueve la innovación tecnológica como motor de competitividad y sostenibilidad.…
Data Scientist leading machine learning projects for credit risk scorecards (origination, credit limits, collections) with full-cycle model development using SQL, Python, and ML libraries like XGBoost and scikit-learn.
Data Scientist at Sage, an academic publisher, building and deploying AI/ML solutions—NLP, Computer Vision, and recommender systems—using Python, R, SQL, and Azure cloud services.
Мы команда на стыке андеррайтинга и моделирования риска, которая создает прорывные решения для привлечения новых клиентов и раскрытия страхового потенциала бизнеса на основе данных и ИИ-технологий. Мы собираем все…
AI/ML Engineer designing, deploying, and sustaining production ML models, NLP/genAI solutions, and real-time decision-support systems for a SOCOM mission partner using Python, ML frameworks, and MLOps/DevSecOps practices in secure environments.
Leads a growing team of applied ML scientists to develop and deploy fraud detection and identity verification models for SentiLink’s fintech solutions, driving product strategy and technical decisions while ensuring AI safety and data governance.
Leads a growing team of applied ML scientists to develop and deploy fraud detection/identity verification models for US financial institutions, balancing technical execution, mentorship, and product strategy in fintech risk solutions.
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