[All remote jobs](https://jobicy.com/jobs.md)[![Signifyd logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/9be4f098-221.jpg)](https://jobicy.com/company/signifyd.md)[Signifyd](https://jobicy.com/company/signifyd.md) # Data Scientist II Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/signifyd.md)ShareRemote from[UK](https://jobicy.com/job-region/uk.md)SalaryUndisclosedDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceSeniorPublished30 Sep 2026Apply before30 Oct 2026Listing views38Application actions1Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. Signifyd is hiring a Data Scientist II for its Applied Decision Science team to develop and improve production machine-learning models and decisioning tools for e-commerce fraud prevention. The role owns the end-to-end lifecycle of hypotheses and models, including experimentation, deployment, evaluation, and automation of manual risk-management work. It requires strong Python, SQL, machine learning, statistics, and distributed-data experience with Spark, Databricks, and GCP. The successful candidate will collaborate with business, risk, sales, customer success, data science, and machine-learning engineering stakeholders, while participating in a rotating weekend on-call schedule. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 4/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 4/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a mid-level production data science position requiring both rigorous modeling expertise and practical ownership of deployed fraud decisioning systems. The combination of experimentation, distributed data tooling, cross-functional communication, and on-call responsibility makes the role technically and operationally demanding. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianMarket rate$145,000US market range$120k–$175k0$193k AI insightNo salary or pay range is disclosed in the posting. These figures are estimated annual USD base-salary benchmarks for a US-market Data Scientist II with 3+ years of experience, production ML responsibilities, and distributed analytics experience; bonus, equity, and location differentials may change total compensation. ## Core skills Skills and capabilities most closely associated with this opportunity. [Machine Learning](https://jobicy.com/jobs?search_keywords=Machine%20Learning.md)[Fraud Detection](https://jobicy.com/jobs?search_keywords=Fraud%20Detection.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Statistics](https://jobicy.com/jobs?search_keywords=Statistics.md)[Experiment Design](https://jobicy.com/jobs?search_keywords=Experiment%20Design.md)[A/B Testing](https://jobicy.com/jobs?search_keywords=AB%20Testing.md)[Apache Spark](https://jobicy.com/jobs?search_keywords=Apache%20Spark.md)[Databricks](https://jobicy.com/jobs?search_keywords=Databricks.md)[Google Cloud Platform](https://jobicy.com/jobs?search_keywords=Google%20Cloud%20Platform.md) Sample interview questionsDescribe how you would evaluate whether a new fraud model improves the current decisioning process.I would define success metrics across fraud loss, approval rate, false-positive rate, customer friction, and operational impact. I would validate offline performance on temporally appropriate holdout data, then use a controlled production experiment where feasible, monitoring metric shifts by merchant, segment, and risk band before making a rollout decision. How would you handle class imbalance in a fraud-detection model? I would first confirm that the label definition and sampling process reflect the real decision environment. Depending on the model and data volume, I could use class weights, carefully designed over- or under-sampling, threshold optimization, and precision-recall-focused evaluation; I would also assess calibration because decision thresholds often drive business outcomes. Tell us about an automation opportunity you would look for in a risk-management workflow. I would map recurring analyst tasks and identify work with consistent inputs, rules, and measurable outcomes. For example, I might automate alert triage or performance reporting with a pipeline that aggregates relevant signals, flags statistically meaningful changes, and routes exceptions for human review, while retaining auditability and monitoring. What practices would you use to make a Python machine-learning workflow production ready? I would use version-controlled, modular code with unit and integration tests, reproducible feature definitions, documented data contracts, and peer review. I would also add model and data-quality monitoring, logging, rollback procedures, and clear ownership for retraining or incident response. How would you explain a model-performance trade-off to a sales or customer-success stakeholder? I would avoid unnecessary modeling jargon and frame the trade-off in business terms, such as the balance between approving more good orders and limiting fraud exposure. I would use a concise visual or concrete example, quantify the expected impact and uncertainty, and explain what guardrails and monitoring will be used after deployment. Opportunity details ## About this role. At Signifyd, we help merchants confidently grow their businesses by building trusted relationships with their customers. Our advanced technology, combined with a team genuinely invested in our clients’ success, creates frictionless shopping experiences, approving more good orders, protecting revenue, and keeping customers happy. Trusted by thousands of leading merchants across more than 100 countries, we securely process billions of transactions each year. Our people are the heart of everything we do, driving our mission forward with commitment, empathy, and creativity. Join us on our mission to empower confident, fraud-free commerce by helping online retailers provide superior customer experiences and eliminate fraud. Learn about our company values [here](https://www.signifyd.com/about/#values)! The Applied Decision Science (ADS) team builds production ML models and risk management tools that are the core of Signifyd’s product. We help businesses of all sizes minimize their fraud exposure and grow their sales. We improve the e-commerce shopping experience for everyone by reducing the friction experienced by good buyers and blocking fraudulent purchase attempts. ADS builds and manages the entire decision stack – from designing and deploying the ML models that assess the riskiness of a transaction, to building the tools the Risk team uses to manage and fight fraud. We seek to standardize and automate repetitive work so we can spend more time on experiments and high-leverage projects. We value collaboration and team ownership. Data scientists in Signifyd are true “full stack” operators, requiring knowledge of how transaction information received via our API traverses its way through our system and into the models we are responsible for building. When you test a hypothesis at Signifyd, you’re responsible for the end-to-end development, deployment, and evaluation process. This is a massive responsibility, and no one should feel like they’re solving a hard problem alone. Together we help each other develop our skillsets through peer review of experiments and code, group paper study to deepen our machine learning and statistical understanding, and frequent knowledge-sharing through live demos, write-ups, and cross-team projects. All team members are expected and encouraged to weigh in as an external reviewer on a peer’s idea or approach, regardless of level. A couple quick notes on the Signifyd culture: * We’re no stranger to remote work. Most of our workforce (ICs and leaders) are primarily remote. We tend to gather individual teams together once a year. There is no travel requirement for this role. * We are heavy Slack users. * We are heavy users of generative AI tools. We dislike token-maxxing, but enjoy the expansion of capabilities that have come with genAI. We ask that during the interview you don’t use genAI, as we want to know what you know. Responsibilities: * Partner with the Business Unit Lead and their merchant portfolio to identify gaps in decisioning performance and implement solutions, with guidance from senior team members. * Utilize existing, or build net new production machine learning models that identify fraud, in collaboration with other data scientists and machine learning engineers. * Identify and build automation that reduces repetitive manual work. * Run experiments to identify optimal decisioning strategies, balancing complexity and performance. * Communicate complex ideas to a variety of audiences, from Customer Success and Sales, to limited interactions with external customers. * Write production and offline analytical code in Python. * Work with distributed data pipelines in Spark/Databricks/GCP. Requirements: * A degree in computer science or a comparable analytical field. * 3+ years of post-undergrad work experience required. * Strong verbal and written communication skills. * Strong machine learning and statistical background. * Write code and review others’ in a shared codebase in Python. * Practical SQL knowledge. * Design experiments and collect data. * Experience with distributed analytics and data tooling such as Spark and Databricks. * This role has on-call shifts, as part of our weekend rotation, Fri/Sat/Sun. While the number of shifts is subject to change, currently it works out to about six weekends a year. Nice to Have: * Previous work in fraud, payments, or e-commerce. * Data analysis in a distributed environment. * A passion for writing well-tested production-grade code. * Experience with AI coding agents and automation. * Experience of running A/B tests in production environments. * An advanced degree. #LI-Remote Our UK benefits: * Stock Options * Annual Performance Bonus or Commissions * Pension matched up to 8% * ‘Day one’ access to great health, dental and optical insurance scheme * Generous annual leave plus public holidays * Cycle to Work Scheme * Enhanced maternity and paternity leave (12 weeks full-pay for mums & dads, plus 12 weeks half-pay for mums) * Regular paid social events organized by our social committee * Mental wellbeing resources * Dedicated learning budget through Learnerbly We are committed to equality of opportunity for all staff and applications from individuals are encouraged regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion or belief and marriage and civil partnerships. We also want to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process. [Signifyd’s Applicant Privacy Notice](https://drive.google.com/file/d/1HSnMY6HGjB1FNRX4Ez9bUre5mrPPcHIq/view?usp=sharing) Show more [Apply now >](https://jobicy.com/jobs/154273-data-scientist-ii.md) > Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. 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