FICO (NYSE: FICO) is a leading global analytics software company, helping businesses in 100+ countries make better decisions. Join our world-class team today and fulfill your career potential!The Opportunity The myFICO (Scores B2C) engineering team is seeking a Lead Data Scientist to build and run machine learning and Generative AI solutions in our consumer applications. This lead-level software engineering role builds the data pipelines that prepare large datasets for modeling, develops ML models and puts them into production with monitoring and retraining, and measures business impact through experimentation. You will also set ML engineering best practices for the team. What You’ll Contribute <ul><li>Build and maintain Python data pipelines that ingest, clean, and transform large datasets into reliable, analysis-ready data and ML features.</li></ul><ul><li>Profile and validate data, and put quality checks in place so models and analyses can be trusted.</li></ul><ul><li>Develop machine learning models, such as propensity, churn, segmentation, and forecasting, from problem framing through evaluation.</li></ul><ul><li>Deploy models to production in AWS for batch and real-time scoring, monitor performance and drift, and automate retraining.</li></ul><ul><li>Design, evaluate, and improve LLM prompts, and integrate Generative AI capabilities into existing applications.</li></ul><ul><li>Design and analyze A/B tests to measure business impact, and explain results to product and marketing partners.</li></ul><ul><li>Lead design discussions and code reviews, mentor engineers and analysts, and set ML engineering best practices.</li></ul><ul><li>Partner with database engineering, product management, and InfoSec to build secure, compliant solutions that handle sensitive consumer data responsibly.</li></ul><ul><li>Use AI coding assistants and agentic workflows, such as Claude Code, Cursor, and GitHub Copilot, to accelerate delivery while reviewing and refining their output. </li></ul>What We’re Seeking <ul><li>Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field, with demonstrated experience in data science, machine learning engineering, or applied AI, including models running in production.</li></ul><ul><li>Strong Python for data engineering and ML (pandas, NumPy, scikit-learn, PySpark), with comfort working in Jupyter notebooks.</li></ul><ul><li>Proven experience building data pipelines and processing large datasets with Spark, Redshift, or similar technologies, plus expert SQL skills for complex queries on large datasets.</li></ul><ul><li>Hands-on experience with ML frameworks such as XGBoost, TensorFlow, or PyTorch.</li></ul><ul><li>Experience operationalizing ML models, including deployment, monitoring, retraining, and CI/CD (SageMaker, MLflow, Docker, or similar), and running data and ML workloads in AWS (S3, Glue, Lambda, Bedrock, or similar).</li></ul><ul><li>Experience with LLMs (Claude, OpenAI GPT, or similar), including prompt design, evaluation, and deploying Generative AI solutions in production.</li></ul><ul><li>Strong grounding in statistics, experimental design, and hypothesis testing.</li></ul><ul><li>Production ownership, including code review, release management, and mentoring, with the ability to explain technical results to non-technical partners.</li></ul><ul><li>Experience with RAG workflows, vector stores, MCP server integrations, LLM fine-tuning, workflow orchestration (Airflow, Step Functions), or regulated consumer data such as credit and financial services is a plus. </li></ul>Our Offer to You <ul><li>An inclusive culture strongly reflecting our core values: Act Like an Owner, Delight Our Customers and Earn the Respect of Others.</li></ul><ul><li>The opportunity to make an impact and develop professionally by leveraging your unique strengths and participating in valuable learning experiences.</li></ul><ul><li>Highly competitive compensation, benefits and rewards programs that encourage you to bring your best every day and be recognized for doing so.</li></ul><ul><li>An engaging, people-first work environment offering work/life balance, employee resource groups, and social events to promote interaction and camaraderie.</li><li>The targeted base pay range for this role is: $105,000 to $165,000 with this range reflecting differences in candidate knowledge, skills and experience. </li></ul>Why Make a Move to FICO?At FICO, you can develop your career with a leading organization in one of the fastest-growing fields in technology today – Big Data analytics.  You’ll play a part in our commitment to help businesses use data to improve every choice they make, using advances in artificial intelligence, machine learning, optimization, and much more. FICO makes a real difference in the way businesses operate worldwide:•    Credit Scoring — FICO® Scores are used by 90 of the top 100 US lenders.•    Fraud Detection and Security — 4 billion payment cards globally are protected by FICO fraud systems.•    Lending — 3/4 of US mortgages are approved using the FICO Score.Global trends toward digital transformation have created tremendous demand for FICO’s solutions, placing us among the world’s top 100 software companies by revenue. We help many of the world’s largest banks, insurers, retailers, telecommunications providers and other firms reach a new level of success. Our success is dependent on really talented people – just like you – who thrive on the collaboration and innovation that’s nurtured by a diverse and inclusive environment. We’ll provide the support you need, while ensuring you have the freedom to develop your skills and grow your career.  Join FICO and help change the way business thinks!Learn more about how you can fulfil your potential at <a href="http://www.fico.com/Careers">www.fico.com/Careers</a>FICO promotes a culture of inclusion and seeks to attract a diverse set of candidates for each job opportunity. We are an equal employment opportunity employer and we’re proud to offer employment and advancement opportunities to all candidates without regard to race, color, ancestry, religion, sex, national origin, pregnancy, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Research has shown that women and candidates from underrepresented communities may not apply for an opportunity if they don’t meet all stated qualifications. While our qualifications are clearly related to role success, each candidate’s profile is unique and strengths in certain skill and/or experience areas can be equally effective. If you believe you have many, but not necessarily all, of the stated qualifications we encourage you to apply.Information submitted with your application is subject to the FICO Privacy policy at <a href="https://www.fico.com/en/privacy-policy">https://www.fico.com/en/privacy-policy</a>

Software Engineering - Lead Data Scientist

<h2>Job Description:</h2>Building trusted markets — powered by our people At Cboe Global Markets, we inspire our people to solve complex challenges together because what we do matters. We provide the financial infrastructure that powers the global economy. As a leading provider of market infrastructure and tradable products, Cboe delivers cutting-edge trading, clearing and investment solutions to market participants around the world.  We're building meaningful ways to support professional and personal development while strengthening the trust we've earned as a global market leader. Our teams are empowered to share ideas, actively pursue them and bring on a challenge. As champions of internal mobility and access to opportunity, we encourage our people to “go for it” and equip our managers with the training to coach their teams to the next level. We strive to provide employees a safe space to network, share ideas and create opportunities.  To support strong partnership and team connection, this role follows a four day in office work model.  Location Overview: Cboe HQ is located in the historic Old Post Office district, it’s a landmark that blends classic architecture with modern amenities. The building features expansive spaces with high ceilings and large windows, offering an abundance of natural light and panoramic views of the city skyline and the Chicago River.  With its prime location in the heart of downtown, the OPO Building provides easy access to major transportation hubs, including Union Station and multiple CTA lines, making it convenient for commuters. The building is home to a variety of amenities, including restaurants, a fitness center, and collaborative workspaces, creating a vibrant and dynamic work environment in one of Chicago's most iconic areas.  Role Overview Cboe Clear U.S. (CCUS) is a regulated clearinghouse. We clear the event contracts and prediction markets listed on Cboe's exchanges, and we are building toward tokenized collateral, 24x7 operation, and the infrastructure that carries traditional finance onto DeFi rails.  CCUS Software Engineering is a high trust environment. Failure leads to inquiry rather than blame. Working across team boundaries is expected rather than tolerated. We solve the problem, then we write the code. Design documents and architecture decision records come first. The engineers we value most close their feedback loop. They write tests, and they instrument what they ship so it fails fast, explains itself in production, leaves an audit trail and rolls back cleanly.  The DevEx Engineer builds the pipelines, tooling and observability every other engineer here depends on. You would be one of the first engineers on a new developer experience team, which means you help choose the tooling and set the standards rather than arrive after those decisions are made. That scope is unusual for an individual contributor role and it is the strongest reason to take this job.  Your responsibilities will be: <ul><li>Building and maintaining our CI pipelines in GitHub Actions, and integrating them with the platform team's deployment tooling. </li></ul><ul><li>Owning the Helm charts and values that define how our services run in each environment. </li></ul><ul><li>Instrumenting those pipelines to produce real metrics on our software delivery lifecycle. </li></ul><ul><li>Wiring observability into our microservices so engineers can diagnose behavior in production rather than reproduce it locally, including logging, tracing and retention. </li></ul><ul><li>Defining service level objectives for the services this team provides, and holding them to an error budget. </li></ul><ul><li>Making the path to production push button and reversible, so releases and rollbacks are routine, automated and low risk. </li></ul><ul><li>Creating tooling that measurably improves how quickly and safely other engineers ship. </li></ul><ul><li>Deploying and operating containerized services on Kubernetes. </li></ul><ul><li>Managing infrastructure as code and keeping environments consistent and reproducible. </li></ul><ul><li>Participating in incident response and turning findings into durable fixes rather than repeat tickets. </li></ul><ul><li>Contributing to disaster recovery testing and the validation of recovery objectives. </li></ul><ul><li>Documenting decisions in architecture decision records so choices stay visible to other teams. </li></ul> Required: <ul><li>Supporting developer experience across the delivery lifecycle, from build and test through deployment and observability </li></ul><ul><li>Experience building and operating production application services, in Java or a comparable language, before moving into developer tooling </li></ul><ul><li>Instrumenting services and pipelines for observability, including the metrics, logs and traces that make runtime behavior visible </li></ul><ul><li>Defining service level objectives and running to an error budget, with alerting that reflects user impact rather than machine noise </li></ul><ul><li>Reducing deployment pain through automation, so changes reach production on a repeatable path with a low change failure rate and fast time to restore service </li></ul><ul><li>A bias toward automating repeated work permanently rather than performing it twice </li></ul><ul><li>Strong Linux fundamentals and comfort operating containerized services on Kubernetes, Nomad or similar orchestrators </li></ul> Preferred: <ul><li>Proficiency in Python, Terraform and YAML, which is what most of this work is actually written in </li></ul><ul><li>Container runtimes such as Docker or Podman </li></ul><ul><li>GitOps deployment workflows </li></ul><ul><li>Building CI pipelines and integrating them with deployment tooling you did not write </li></ul><ul><li>Shell scripting and comfort automating around tools that lack an API </li></ul><ul><li>Incident response and disaster recovery testing </li></ul><ul><li>Financial markets infrastructure or other regulated, latency-sensitive systems </li></ul> Nice to have: <ul><li>Cloud platforms including AWS, Azure or GCP </li></ul><ul><li>AI-assisted development tooling </li></ul><ul><li>Working SQL and comfort with PostgreSQL </li></ul><ul><li>Experience standing up a platform function from scratch </li></ul> Current technology stack: Java on Kubernetes. Application code and CI pipelines live in GitHub with GitHub Actions. Container images and build artifacts live in registries such as Harbor and Artifactory, and Helm charts are deployed by ArgoCD from a GitOps repository. PostgreSQL, Kafka and Linux. This is representative rather than exhaustive. Our platform team runs the deployment platform on its own tooling, in its own repositories, so a real part of this role is integrating cleanly across that boundary and telling them what our application developers need. You do not need experience with every technology in our environment. We hire for competencies over pedigree, so if you have built similar systems and learn quickly, we encourage you to apply.  Minimum Work Experience: 5+ years in platform engineering, developer experience, infrastructure or reliability engineering Minimum Education: Bachelor's in Computer Science or a related discipline, or equivalent practical experience   This position is not eligible for visa sponsorship. Candidates must be legally authorized to work in the United States without the need for employer sponsorship now or in the future.  Salary Ranges (applicable for US locations only)At Cboe, we are committed to providing a competitive, transparent, and market‑informed total rewards program. The anticipated base salary range for this role is $102,850-$133,100, with actual compensation determined by job‑related factors such as skills, relevant experience, education, internal alignment, and location.  This role may also be eligible for annual incentive compensation and, where applicable, participation in Cboe's long-term equity programs.Additional information about Cboe's total rewards program, including benefits and other compensation components, can be found here: <a href="https://careers.cboe.com/us/en/benefits-and-perks">Total Rewards at CBOE</a>.​    Any communication from Cboe regarding this position will only come from a Cboe recruiter who has a @cboe.com email or via LinkedIn Recruiter. Cboe does not use any other third party communication tools for recruiting purposes.

DevEx Engineer

SummaryGuidewire’s Generative AI (GenAI) team sits within Product Strategy and plays a critical role in shaping the future of our cloud and AI-powered platform for P&amp;C insurers worldwide. We partner closely with Product, Engineering, and Go-to-Market teams to embed AI, cloud, and data capabilities across the portfolio, enabling secure, scalable, and reliable solutions for our customers. You’ll join a highly collaborative, hands-on engineering culture focused on experimentation, learning, and shipping production-grade AI at scale. As a Senior ML Engineer, Generative AI, you will be a technical leader driving the design, development, and operation of Guidewire’s end-to-end GenAI solutions and Large Language Model (LLM) capabilities. You will own critical components of our LLM infrastructure, from data pipelines and prompt engineering through fine-tuning, deployment, and monitoring of models in production. This role is ideal for someone who wants to shape next-generation AI solutions that directly power insurance workflows, support our Agentic AI product vision, and help deliver measurable outcomes for customers globally.Job Description<h3>What you’ll do</h3><ul><li>Lead the design, implementation, and evolution of Guidewire’s GenAI and LLM products, including data ingestion, feature pipelines, model training, fine-tuning, deployment, and monitoring on AWS (e.g., S3, EC2, RDS, SageMaker).</li><li>Architect and build robust ML/LLM pipelines that power high-impact use cases such as claim summarization, underwriting assistance, pricing and rating intelligence, and developer productivity tools across our product portfolio.</li><li>Develop and optimize LLM solutions using techniques such as prompt engineering, retrieval-augmented generation (RAG), vector databases, and fine-tuning to deliver reliable, safe, and high-performing experiences for insurance users.</li><li>Collaborate with Product Strategy, PDO, and Professional Services teams to align GenAI capabilities with the broader Product VPMOM, Agentic AI product roadmap, and customer adoption goals (including Claims Summary, Underwriting Assistant, Codelift, and other GenAI “lifts”).</li><li>Establish and apply ML Ops best practices for CI/CD, experimentation, evaluation, observability, and responsible AI, ensuring models are auditable, secure, and production-ready at scale.</li><li>Mentor and coach engineers and data scientists, conduct code and design reviews, and champion technical excellence, including performance, reliability, and cost efficiency of AI workloads.</li><li>Partner with cross-functional teams (Security, Finance, BizTech, GTM) to ensure AI solutions adhere to data governance and security controls, and contribute to Guidewire’s mission to transform how P&amp;C insurers do business through cloud, analytics, and AI.</li><li>At Guidewire, we foster a culture of curiosity, innovation, and responsible use of AI—empowering our teams to continuously leverage emerging technologies and data-driven insights to enhance productivity and outcomes.</li></ul> <h3>What you’ll bring</h3><h3>Required</h3><ul><li>Demonstrated ability to embrace AI and apply it to your current role as well as data-driven insights to drive innovation, productivity, and continuous improvement.</li><li>5+ years of professional experience in Machine Learning and/or Data Science, including end-to-end delivery of production ML systems.</li><li>Deep expertise in Python and experience building scalable ML/LLM services and pipelines, ideally on AWS using services such as S3, EC2, RDS, and SageMaker.</li><li>Strong understanding of ML Ops practices for model development, deployment, monitoring, and lifecycle management (including CI/CD for ML, experiment tracking, model registries, and drift detection).</li><li>Hands-on experience with classical and gradient-boosting models (such as GLM, Random Forest, and XGBoost) and their application to real-world business problems.</li><li>Deep understanding of neural networks and transformer-based architectures for LLMs and chat models, including familiarity with open-source foundation models and their fine-tuning and inference.</li><li>Experience with prompt engineering, RAG and related LLM architecture patterns, and vector databases for semantic search and retrieval.</li><li>Solid knowledge of evaluating and monitoring LLM performance using NLP and LLM-assisted metrics, with a focus on safety, robustness, and user experience.</li><li>Demonstrated technical leadership: driving design decisions, leading complex engineering efforts, mentoring peers, and conducting thoughtful code and architecture reviews.</li><li>*****MUST HAVE GUIDEWIRE EXPERIENCE*******</li></ul> <h3>Preferred</h3><ul><li>Bachelor’s or Master’s Degree in Computer Science, or equivalent practical experience.</li><li>Experience building data pipelines and features using SQL, Spark, or AWS Glue.</li><li>Experience with containerization and orchestration (Docker, Kubernetes) and creating backend APIs to expose ML/LLM services.</li><li>Familiarity with CI/CD and infrastructure-as-code practices and tools such as TeamCity and Terraform.</li><li>Background in insurance, banking, or financial services, or interest in becoming deeply fluent in P&amp;C insurance to better shape high-value AI and GenAI use cases.</li></ul> <h3>Your Impact</h3>We believe in clarity and setting you up for success. In your first months, you’ll immerse yourself in Guidewire’s Product Strategy and GenAI roadmap, learn our cloud and data platform, and take ownership of one or more core components of the GenAI platform such as data pipelines, evaluation frameworks, or a flagship LLM-powered feature. Within six months, you’ll be leading the design and rollout of new GenAI use cases across products like Claims Summary, Underwriting Assistant, and developer tooling, delivering measurable “GenAI lifts” that improve efficiency, accuracy, and user experience for our customers. Your work will directly advance Guidewire’s mission to transform how P&amp;C insurers operate with cloud and AI, enabling secure, scalable, and impactful AI solutions that support billions of dollars in insurance transactions and help shape the future of the industry worldwide. <h3>What’s in it for you</h3>The people we employ give their all, and in return, we offer flexibility wherever we can, such as:<ul><li>Flexible work environment.</li><li>Health and wellness benefits.</li><li>Paid time off programs including volunteer time off.</li><li>Market-competitive pay and incentive programs.</li><li>Continual development and internal career growth opportunities.</li></ul> You will also participate in our in-person orientation process, which is part of how we build connection, collaboration, and a shared understanding of Guidewire’s mission to combine digital, core, analytics, and AI to transform how P&amp;C insurers do business.&amp;#xa;The US base salary range for this full-time position is $162,000 - $258,000. Your base pay will depend on your experience, skills, education, training, and location among other factors. All full-time positions or part-time roles working 30 hours or more a week at Guidewire are eligible for benefits that support their health and well-being including health, dental, and vision insurance, paid time off, and a company sponsored retirement plan. In addition, some roles may be eligible for the annual company bonus plan, commissions, and/or long term incentive awards which are contingent on a variety of factors including, but not limited to, company and employee performance.&amp;#xa;&amp;#xa; About Guidewire Guidewire is the platform P&amp;C insurers trust to engage, innovate, and grow efficiently. We combine digital, core, analytics, and AI to deliver our platform as a cloud service. More than 540+ insurers in 40 countries, from new ventures to the largest and most complex in the world, run on Guidewire. As a partner to our customers, we continually evolve to enable their success. We are proud of our unparalleled implementation track record with 1600+ successful projects, supported by the largest R&amp;D team and partner ecosystem in the industry. Our Marketplace provides hundreds of applications that accelerate integration, localization, and innovation. For more information, please visit www.guidewire.com and follow us on Twitter: @Guidewire_PandC. Guidewire Software, Inc. is proud to be an equal opportunity and affirmative action employer. We are committed to an inclusive workplace, and believe that a diversity of perspectives, abilities, and cultures is a key to our success. Qualified applicants will receive consideration without regard to race, color, ancestry, religion, sex, national origin, citizenship, marital status, age, sexual orientation, gender identity, gender expression, veteran status, or disability. All offers are contingent upon passing a criminal history and other background checks where it's applicable to the position. Guidewire is proud to be a disability inclusive employer. We are committed to providing individualized accommodations and support to candidates for any part of our hiring process. If you think you may need disability-related accommodations, please email EmployAbility at accommodations-gw@employ-ability.org.uk, our disability partner, or <a href="https://calendar.app.google/Pz47ZoQHihFTJugX8">schedule a call with an EmployAbility expert</a> (calendar booking slot) for a confidential conversation.

Christian Docker Jobs

Explore top Christian Docker jobs at leading faith-friendly companies.