Senior Data Scientist, AI Evaluation

About Bluevine Bluevine is the largest small business banking platform in the U.S., redefining how entrepreneurs manage their money. We create modern financial solutions, from checking and lending to payments and beyond, designed to help small business owners grow, thrive, and take control of their financial future. Our best-in-class technology, advanced security, and deep understanding of the small business community give our customers the confidence to focus on what they do best. Since 2013, we’ve supported more than 750,000 small businesses nationwide. Backed by leading investors like Lightspeed Venture Partners, Menlo Ventures, 83North, and Citi Ventures, our 500+ person global team shares one mission: to give small businesses the financial tools they need to succeed. We’re innovators driven by big ideas, collaboration, and real impact. Here, you’ll have the freedom to take ownership, grow your career, and make a difference for small business owners across America. Ready to shape what’s next? This is a hybrid role . At Bluevine, we pride ourselves on our collaborative culture, which we believe is best maintained through in-person interactions and a vibrant office environment. All of our offices have reopened in accordance with local guidelines, and are following a hybrid model. In-office days will be determined by location and discipline. Key Responsibilities: Generative AI Research: Explore and evaluate Large Language Models (LLMs) and emerging generative AI techniques to identify impactful applications in data science. Model Fine-Tuning & Adaptation: Design and execute experiments to fine-tune or customize foundational models using domain-specific and internal datasets. Applied Generative AI Solutions: Leverage generative AI to enhance traditional machine learning use cases such as risk modeling, fraud detection, and customer analytics. Prompt Engineering & Evaluation: Develop effective prompting strategies and build robust evaluation and benchma

Banking hasn't changed much in decades. We're changing that. One product at a time. Lunar is a Nordic challenger bank building the future of financial life with AI at the core. Our engineers, designers, and product people work on problems that actually matter. Making money simpler, smarter, and more rewarding for millions of people across the Nordics. Fully licensed and founded in 2015, with offices in Copenhagen, Aarhus and Stockholm. We move fast, we build with purpose, and we're just getting started. As our new (Senior) Data Scientist you'll join our team based in Aarhus, reporting to Eugene, our Senior Engineering Manager, working to bring data and machine learning into how we prevent fraud, manage risk, and grow the business. What will you do? Design, build, and deploy machine learning and statistical models across fraud detection, transaction monitoring, loan risk assessment, customer risk scoring, and sales and lead generation Build and operate experimentation and evaluation frameworks — using tools like MLflow and Metaflow — with strong test sets and benchmarks across projects Dive into data analysis and feature engineering to keep pushing model performance further Partner closely with data engineers, analysts, and business stakeholders to define requirements and turn insight into decisions Document models, methodologies, and results clearly, and bring the latest ML and GenAI advances into how Lunar builds What are we looking for in you? Experience developing and deploying machine learning models in a production environment Proficiency in Python and relevant ML libraries (e.g., scikit-learn, TensorFlow, PyTorch) Experience with cloud-based ML platforms such as AWS SageMaker or Kubeflow Solid grounding in machine learning, statistical modeling, and data analysis techniques — experience in financial services or another regulated industry is a plus Strong problem-solving and communication skills, with the ability to translate technical concepts into business in

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the Team The Finance Data Science team owns the forecasting systems that power Snowflake’s revenue planning and long-term financial strategy. Our work supports corporate planning, executive decision-making, and investor reporting, and we partner closely with Product and Sales to understand customer behavior and product impact. We operate at the intersection of machine learning, statistical research, and corporate finance, building production-grade forecasting infrastructure that is foundational to how the company plans and operates. The Role As a Senior Data Scientist, you will independently lead high-impact modeling initiatives and build production-ready forecasting systems for core financial metrics. You will work on complex, open-ended problems at the intersection of machine learning and business strategy, translating real-world financial questions into rigorous, scalable models. What You’ll Do Design and implement advanced time-series and probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches, multivariate forecasting). Contribute to internal tooling and shared infrastructure that enables scalable forecasting and analytics. Establish best practices for model evaluation, backtesting, uncertainty quantification, and scenario simulat

Zoox is on an ambitious journey to develop a full-stack autonomous vehicle system for cities. We are seeking a Senior Data Scientist to join a verification and validation team that evaluates safety-critical AI systems. You will join a team of software and data engineers that leverage methods including log data analysis, simulation, and closed-course structured testing. You'll work cross-functionally with AI software, System Design and Mission Assurance, Simulation, Sensors, and other teams to develop, execute, and iterate on validation methods and pipelines. These pipelines evaluate safety-critical systems, are highly visible, and are an important critical path element of launching our service. The ideal candidate brings a hybrid of statistical rigor and engineering mindset to drive clarity from ambiguity, establish new processes, and propel the team forward. This is a deeply technical and hands-on role where you will be expected to be a self-sufficient builder and coder, not just a manager of projects. In this role, you will: Design Evaluation Frameworks: Architect statistical methodologies for safety-critical AI systems to form objective, rigorous conclusions about their performance and reliability. Conduct Robust Analysis: Deliver validation evidence to support increasingly complex operations and identify potential edge-case failures. Inform Strategy: Deliver clear, data-driven insights to development teams to guide system improvement, and to executive leadership to inform milestone-level go/no-go decisions. Define Metrics: Drive alignment across engineering teams on performance metrics and data extraction strategies. Lead the Lifecycle: Manage all phases of evaluation including prototyping, requirements capture, design, implementation, and validation. Scale Pipelines

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it's medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity. As a Senior Data Scientist, you will build and own machine learning models that power core prediction problems across the FourKites platform — including ETA/ATA forecasting and message-based status extraction. You will work end-to-end, from data pipeline to production deployment and monitoring, turning noisy real-world logistics data into models that run at scale and directly move the needle on customer outcomes. You will work closely with product, engineering, and operations teams, hands-on building and shipping models yourself while also guiding the technical direction of other data scientists on the team. What you'll be doing: Design, build, and productionize ML models for problems like ETA/ATA prediction, using regression, classification, and time-series forecasting techniques Develop NLP/LLM-based extraction pipelines for message-based ETA and status updates (text extraction, entity recognition) Own models end-to-end: data pipeline → training → deployment → monitoring → retraining Work with noisy, real-world logistics and supply chain data (GPS pings, check calls, carrier data) rather than clean, pre-processed datasets Diagnose gaps between offline evaluation performance and live production accuracy, and drive fixes Build and maintain automated training/retraining pipelines using orchestration tools such as Airflow Set up and maintain model monitoring and observability (e.g., Grafana) to catch drift and degradation proactively Replace manual or rule-based processes with ML-driven automation (e.g., automating manual check calls) Translate model performance improvements into busin

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly within the United States. If you happen to live close to one of our physical office locations (San Francisco, Los Angeles, New York City & Chicago) our doors are open for you to come into the office as often as you'd like. Reddit is poised to innovate and grow like never before, and Safety is a critical accelerant of that growth. The Safety org is Reddit’s central Trust & Safety organization, protecting users from bad experiences by stopping harmful content, behaviors, and abuse across the platform. We are looking for a Senior Data Scientist to lead ads fraud detection and scaled enforcement within Safety. You will partner closely with Ads Product, Engineering, Machine Learning, Operations, Policy, Legal, and fellow Safety data scientists to identify emerging ads fraud, define rigorous measurement and evaluation standards, and turn investigations into durable signals, models, rules, and enforcement pipelines. This is a high-impact role with exceptional opportunity for ownership and growth: as an early leader in a greenfield space, you will help define the strategy, shape cross-functional roadmaps, build foundational capabilities, and expand your scope as Reddit’s ads integrity program matures. Responsibilities Lead the measurement and detection strategy for ads fraud by defining fraud taxonomies, labels, sampling plans, metrics, and evaluation frameworks that make performance measurable and defensible. Analyze la