Senior Data Scientist, Decisions - Risk

Lyft

At Lyft, our mission is to improve people's lives with the world's best transportation. To accomplish this, we start with our community by creating an open, inclusive, and diverse organization.   About the Team The Risk Tech engineering organization is committed to tangibly reducing accident frequency, saving lives, and managing costs to enhance the safety and affordability of rides. Claim Management is a core financial function for Lyft. Each claim touches complex workflows, multiple stakeholders, sensitive data, financial reserves, regulatory processes, and significant financial liabilities. This role offers the opportunity to define a leading claims management system for the industry. Our vision is to establish a single, Unified Risk Platform where comprehensive claims workflows across all business lines are efficiently administered, communications are consolidated, and data is structured to facilitate data-driven insights and decisions.This enables cost-efficient claims operations, mitigates risks and expenses as Lyft scales, and ensures people receive assistance proactively and accurately.   About the Role We are seeking a Senior Software Engineer to contribute to the technical direction, drive architectural decisions, and lead the development of a highly reliable, scalable, and intelligent Risk Management Information System that powers our insurance platform. You will collaborate with passionate colleagues from Engineering, Data Science, Product and Claim Operations to deliver end-to-end solutions.  RESPONSIBILITIES: * Define and drive the long-term technical roadmap for claims management systems, aligning priorities with Product, Claim Operations, Data Science, and other stakeholders. * Provide architectural leadership, make informed design tradeoffs, and guide strategic decisions across multiple engineering teams. * Understand claim handling workflows, identify bottlenecks and multiply their productivity by driving platform innovations and resolving pain points with AI automation solutions * Deliver scalable, reliable, high quality and well-tested solutions and code. * Collaborate closely with Lyft internal teams and external insurance partners to ensure technical alignment and scalable integrations. * Lead code reviews, design reviews, production on-call support and incident triaging process. * Invest in the engineering community through knowledge sharing via brown bags, tech talks, and suggesting improvements to team processes and engineering practices. PREFERRED EXPERIENCE: * B.S., M.S. in Computer Science or related technical field or relevant work experience. * 6+ years of professional experience building scalable distributed systems with high availability, observability and reliability requirements. * Proven ability to build end-to-end products and platforms, collaborating effectively with various stakeholders e.g. Backend, Frontend, Data Engineering, Data Science, Claim Operations, and Product teams. * Strong ability to reason about tradeoffs in system design, architecture, domain modeling, and operational cost. * Experience developing AI features using multimodal LLMs, RAG pipelines, agentic workflows, and other relevant AI frameworks. * Experience driving AI adoption or AI automation tools to enhance development efficiency * Experience improving performance with robust evals,agent tracing tools, fine-tuning LLMs, optimizing RAG pipelines and implementing feedback loops. * Proficiency in Python. Knowledge of React/Next.js and data analysis is a plus. * Experience with data processing frameworks and tools like Spark, Kafka, Airflow and cloud provisioning environments etc. * Strong oral and written interpersonal skills.   EXPERIENCE: * Prior experience in insurance, claims management, workflow orchestration or external vendors is a strong plus. * Has knowledge about AI safety and alignment considerations. * Background in machine learning, NLP, or related fields. * Experience with A/B testing and experimentation frameworks BENEFITS: * Great medical, dental, and vision insurance options with additional programs available when enrolled * Mental health benefits * Family building benefits * Child care and pet benefits * 401(k) plan with company match to help save for your future * In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off * 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible * Subsidized commuter benefits * Monthly Lyft credits and complimentary Lyft Pink membership Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law. Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid The expected base pay range for this position in the San Francisco area is $148,000 - $185,000 , not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Plaid

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. The Embedded Insights team builds machine learning models to enable better internal decision making and to power the Plaid product suite. We are structured as a central team of MLEs and Data Scientists, and embed with partner teams to bring ML models to life. As the first Data Scientist on Plaid’s Embedded Insights team within the Data organization, you will play a foundational role in building the analytics and measurement framework that supports a broad portfolio of internal and customer-facing products. You will partner closely with product, engineering, and machine learning teams to drive data-informed decision making, evaluate product and model performance, and contribute directly to the health and growth of the Plaid network. In this role, you will analyze entities across the Plaid network to better understand behavior patterns and develop metrics and monitoring systems that identify anomalies and emerging risks. You will create dashboards and reporting frameworks that provide clear visibility into machine learning model performance, while also evaluating the impact and value of these models on both customer and internal datasets. A key part of your work will involve translating complex analyses into compelling, actionable narratives for technical and business stakeholders. You will design and analyze experiments, communicate findings across teams, and use data-driven insights to uncover opportunities to improve existing products and expand Plaid’s offerings. Responsibilities: * Applying your expertise in quantitative analysis, data mining, and data visualization to keep the Plaid network safe and improve our product suite. * Informing and influencing product and engineering teams through your data analysis and presentations. * Making long-term data science roadmap decisions like how machine learning and data science iteration should be done at Plaid. * Championing a data-first approach toward decision-making across the entire organization. Qualifications: * 5+ years of industry experience in a Data Science role. * Bachelor's degree or equivalent work experience in Computer Science, Statistics. Engineering, Economics, or a closely related field. * Experience with Payment Risk, Fraud or Trust & Safety. * Deep familiarity with SQL and data visualization tools. * Understanding of modern machine learning techniques, such as classification, clustering, optimization. * Proven ability to tailor your solutions to business problems in a cross-functional team. * Ability to code and iterate independently in Python to conduct exploratory data analysis. * Experience building data pipelines in DBT or Airflow is a plus. Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid! Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com. Please review our Candidate Privacy Notice here. Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

Securitas Intelligent Services AB

Securitas Group Securitas is a world-leading safety and security solutions partner that helps make your world a safer place. By leveraging technology in partnership with our clients, we offer a broad portfolio of value-enhancing services and solutions integrated across the security value chain – from on-site services to advanced monitoring, comprehensive risk prediction and advisory services. With around 322 000 employees in 44 markets, our innovative, holistic approach with local and global expertise makes us a trusted business partner to many of the world’s best-known companies. Benefitting from almost nine decades of deep experience and guided by our values of integrity, vigilance, and helpfulness, we create sustainable value by helping our clients optimize their operations and protect what matters most - their people and assets. AI Team at Securitas At Securitas, our colleagues show up every day to help keep communities and organizations safe. Our job in the AI team is to make sure they're equipped with the best tools and intelligence possible. We are Securitas' Specialized AI Team - the internal center of excellence for advanced, custom AI. We don't work on generic tools or off-the-shelf solutions. We build the AI capabilities that require deep technical and domain expertise, and that directly move the needle on how Securitas operates at scale. About the role You will be a key technical voice in a small, focused team - someone who shapes how we approach problems, not just solves them. You'll lead the design, development, and production deployment of ML and GenAI solutions that turn raw data into actionable intelligence across a range of real-world problems. The stack we work with Python · PyTorch · LLMs (OpenAI, Gemini, Claude, open-source) · RAG pipelines, Hugging Face · Python analytical tools (DuckDB, polars, Pandas, and more) · Streamlit & Dash · Claude Code · GitHub Copilot · React · Databricks · Docker · SQL/NoSQL · Azure/GCP Responsibilities Owning the architecture of LLM-powered pipelines that extract structure and insight from large volumes of unstructured text, such as incident reports, operational logs, client data. Designing and stress-testing end-to-end GenAI architectures (e.g. RAG), prompt strategies, and evaluation frameworks - relevance, faithfulness, hallucination rates, latency tradeoffs - and setting the bar for what "good" looks like on the team. Building and productionizing workforce management models - demand forecasting, shift scheduling optimization, and attrition modeling - that help deploy officers more effectively. Developing client churn models that give the business early, actionable retention signals. Driving the end-to-end ML lifecycle: from problem framing and data strategy through to monitored, production-grade systems. Translating ambiguous business problems into concrete technical roadmaps - and pushing back when the framing is wrong. Mentoring junior data scientists and setting technical standards across the team. Presenting findings, model behavior, and tradeoffs to senior stakeholders clearly and credibly. What you'll bring Must-haves Around 5+ years of professional data science experience, with a clear track record of successes. Deep Python skills and strong software engineering habits - your code is readable, tested, and maintainable. Advanced NLP experience and hands-on work with LLMs at a level beyond prompt experimentation - fine-tuning, evaluation, deployment. A rigorous approach to GenAI evaluation: you've built frameworks to measure output quality, catch failure modes, and make principled tradeoffs with full lifecycle thinking. Experience with MLOps fundamentals: deployment, serving, and monitoring of models, CI/CD, Docker, application and service logging, and reproducible pipelines. Using modern AI coding tools to work as a highly productive data scientist - rapidly exploring ideas, writing and refactoring code, and debugging faster while keeping a critical eye on outputs. Strong analytical instincts - you can tell when a result is too good to be true and you know how to find out why. Communication skills sharp enough to run a stakeholder presentation and a code review on the same day. Nice-to-haves Experience with Databricks for large-scale data processing and collaborative workflows. Familiarity with LLM evaluation frameworks (Ragas, LangSmith, or similar). Hands-on experience with forecasting and optimization problems - scheduling, demand planning, or similar. Experience building interactive data tools for end users, including front-end design, authentication layers, and logging. Background in a domain where decisions have real operational consequences - logistics, healthcare, security, or similar. Working conditions The role is open for candidates based in Malmö or Stockholm (with preference for applicants in Malmö). It's a hybrid working model. What we offer At Securitas we believe in doing the right thing and doing it well. For our customers and our employees. Our employees come from all walks of life and bring with them many talents and perspectives. We aim for diverse representation throughout the company, and we are committed to equal pay, safe working conditions, gender balance and an inclusive work environment with a wide range of skills and development opportunities. If this sounds like the right next step in your professional career, don't hesitate and apply!