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The ideal candidate will be responsible for leading the development and deployment of machine learning models that power key business decisions such as collections models, credit risk scoring, fraud detection, customer segmentation, and personalized financial services.. Masters or Similar in Computer Science, Data Science, Statistics, Applied Mathematics, or a related quantitative field. Expert in Python, SQL, ML libraries (Numpy, Pandas, Scikit-learn, TensorFlow, PyTorch) and techniques (Regression, Decision Trees, Ensembles: XGBoost, GBM, Random Forest, Unsupervised Learning, etc. Knowledge of MLOps frameworks (MLflow, Kubeflow, Airflow, Docker, Kubernetes) is added benefit.. Strong grasp of statistical modeling, optimization, and deep learning techniques.
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure.. 6+ years Life Sciences consulting or industry technology experience driving digital transformation and innovation by delivering impactful data and AI analytics solutions. 1+ years experience leading, managing and delivering complex technical engagements with resources in multiple locations Bachelor's Degree in Data Science, Computer Science, Mathematics or a related field Ability to travel up to 50% on average, based on the work you do and the clients and industries/sectors you serve Limited immigration sponsorship may be available. Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud). Qualified applicants with criminal histories, including arrest or conviction records, will be considered for employment in accordance with the requirements of applicable state and local laws, including the Los Angeles County Fair Chance Ordinance for Employers, City of Los Angeles's Fair Chance Initiative for Hiring Ordinance, San Francisco Fair Chance Ordinance, and the California Fair Chance Act. See notices of various fair chance hiring and ban-the-box laws where available.
A company at the intersection of AI and Life Sciences is looking to expand their highly successful AI Research team.. The company is based in the San Francisco Bay Area, but the role may be open to fully remote.. Libriaries: PyTorch, Tensorflow, Scikit-learn, Pandas. Neural Networks: Graph Neural Networks, CNN. Protein Language Models: AlphaFold, etc.
Design and maintain fraud rules and scoring logic for transaction monitoring systems. Ensure alignment with regulatory expectations, model risk governance, and internal audit requirements. Explore and implement new technologies (e.g., graph analytics, behavioral biometrics, NLP) for advanced fraud detection. Strong command of Python, R, SQL, and data science libraries (pandas, scikit-learn, TensorFlow, etc.. Exposure to real-time fraud systems (e.g., SAS Fraud Management, Actimize, Falcon, etc.)
Fully Remote (onsite in Vinings, GA from Mon-Thurs if converted to FTE). We are seeking a Senior BI Analyst with expertise in Python, SQL, Tableau, and predictive analytics.. You will work with large datasets across SAP and Snowflake environments to deliver strategic insights, with a strong focus on forecasting container arrivals, optimizing inventory levels, and identifying cost-saving opportunities – all in support of a major ERP modernization and the nationwide consolidation of distribution centers.. System Migration : Lead data analysis and reporting for a major migration from a legacy ERP to SAP Warehouse Management, with reporting transitioning to Snowflake.. Python Predictive Analytics : Perform predictive modeling in Python to forecast container arrivals, inventory levels, and other supply chain KPIs.
🚀 Publish, present, and patent high-impact findings in AI and machine learning.. Conduct cutting-edge research in artificial intelligence, including areas such as natural language processing, computer vision, generative models, and reinforcement learning.. Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ACL, CVPR, ICLR) is highly preferred.. Expertise in machine learning, deep learning, or statistical modeling.. Experience with model development using TensorFlow, PyTorch, JAX, or similar frameworks
Broad technical foundation in software engineering and deep learning (through self-study, practical experience, or PhD).. ML: knows the theory and applied side of deep learning, especially computer vision and foundational model architectures (PyTorch, OpenCV, Tensorflow).. Backend: experience designing and building scalable and high availability server-side systems (Python, NodeJS, or Golang).. Cloud: familiarity with DevOps and infrastructure (i.e. Docker, Kubernetes, GPU scheduling) on cloud (i.e. GCP, AWS).. Monitoring: experience with logging systems and monitoring tools such as DataDog, Sentry, and/or CloudWatch
Seeking a Machine Learning Engineer to maintain, enhance, and productionize an existing predictive model that estimates the average duration of construction jobs.. You’ll work with historical workflow data, improve model accuracy, and explore new ML opportunities once the current model is stable.. Python – strong proficiency for data manipulation & model implementation.. Applied Machine Learning – hands-on experience with regression, classification, or similar predictive modeling techniques.. Work with historical workflow data to refine accuracy and reliability.
This role will focus on developing greenfield applications as part of a critical state-wide government healthcare initiative to provide comprehensive mental health services.. Leverage tools like Docker to containerize applications that can be efficiently orchestrated in EKS for deployment in AWS. Leverage open-source technologies and communities, industry trends, emerging technologies, and best practices in web development.. ~PostgreSQL, MySQL) and designing efficient data models. ~ Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching.
Define and implement enterprise-wide AI and quantitative modeling strategy tailored to oil & gas value chains (e.g., asset optimization, drilling, trading, predictive maintenance).. Establish AI governance frameworks that ensure responsible AI adoption, ethical use of data, model risk management, and alignment with evolving regulations.. Prior experience leading AI initiatives in the energy or oil & gas sector, including exploration, refining, or energy trading.. AI certifications (Microsoft, AWS, NVIDIA, Databricks, or equivalent).. Community Association Manager / Business Development Leader Business Analyst/Project Manager (Business Systems Analyst 3) Davis, CA $75,000.00-$135,600.00 3 weeks ago