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+ Bachelor's or Master's degree or equivalent experience and a shown foundation in statistical and data science (e.g. Machine Learning, Predictive analytics, etc.). + Skill with analytic tools ranging from relational databases and SQL to Excel, and Python/R. Experience with Product analytics tools like Amplitude, Content square, Adobe analytics, etc.. + Experience working with on Premise and/or Cloud analytics environments like Hadoop, AWS, Snowflake, etc.. + Experience with data visualization and enablement tools like Tableau, Power BI, etc.
Our newest member of The Social Order family, we are proud to bring Oklahoma City, Spark!. A fast-casual and family friendly concept located in Nichols Hills.. Our menu features classic cheeseburgers, crinkle cut fries, and the best custard in the state.. Stay on the Grass, Have a Nice Day and Eat at Spark!. Employee Assistance Program encouraging mental health for all employees and their households
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.
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
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.
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.)
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.
🚀 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
You’ll lead high-impact client engagements focused on Generative AI, Agentic AI, MLOps, and AI governance frameworks — driving measurable outcomes in upstream, midstream, and downstream operations.. 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).
Together with our Principal Data Scientist, define and drive the data science roadmap in alignment with business and product goals.. 7+ years of experience in data science or advanced analytics, with 2+ years in a leadership role (managing ICs).. Advanced proficiency in Python, SQL, and machine learning frameworks.. Experience with modern data and ML tooling (e.g., Snowflake, dbt, Looker, Hex etc. Unlimited PTO (paid time off)+ the flexibility to enjoy it
Field: Mining Engineering, Industrial Engineering, Operations Research, Artificial Intelligence. As part of the project "Redesign of extraction methods for improving phosphate quality" , we are hiring a postdoctoral researcher to work on rethinking extraction methods at one of OCP Group’s production sites.. This work will require an understanding of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict ore quality and optimize operational decisions.. PhD in Mining Engineering, Industrial Engineering, Operations Research, Data Science, or a related field.. Practical experience in mining or industrial environments (through projects, thesis, or postdoctoral work).