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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.
Comscore's fast-growing Activation business, Proximic, needs a seasoned Data Scientist to help build bring new products to the market by extracting valuable information from large and diverse data sources. A Senior Data Scientist works with the broader Analytics team, as well as Product and Engineering teams, to produce algorithms, models, and tools for organizing, analyzing, and measuring data through visualization tools, reports, technical papers, patents and other means for conveying analysis results. Build a wide variety of models ranging from simple regression to neural networks leveraging LLM embeddings.. Programming experience in R, Python, Scala or SQL as well as Big Data Analytics using Spark or Snowflake.. With a data footprint that combines digital, linear TV, over-the-top and theatrical viewership intelligence with advanced audience insights, Comscore allows media buyers and sellers to quantify their multiscreen behavior and make business decisions with confidence.
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.
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
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