Risk Decision strategist

It starts here. Have a global impact on the world of payments. This role is part of the Risk Systems & Strategy team within the broader organization led by the Chief Risk Officer (CRO). You will focus on the analysis of merchant risk activities for our merchant products, including ecommerce, point of sale and eCash solutions. You’ll identify new risk management and loss mitigation opportunities, optimize existing strategies, develop new ones, minimize false positives, and make clear actionable recommendations that drive decision making. You’ll become an expert on merchant risk and fraud risk data while working closely with the data engineering and data modeling teams. Work will also involve high‑impact strategic projects with business-wide exposure and interactions with C‑Level stakeholders. You will have the space to take ownership of projects and contribute to the domain strategy. You are comfortable working on projects where not everything is defined, generating creative solutions, and involving your manager when support is needed. We follow a hybrid working model, spending an average of three days per week at our office hub. We are considering applications for both our London and Dublin office locations.

Responsibilities

• Undertake deep dive analysis into merchant behaviour to identify patterns, trends, and root causes.
• Make clear recommendations on how to capitalize on opportunities, feeding into and driving the business strategy with insights.
• Apply structured problem solving with the ability to logically break ambiguous problems into constituent parts.
• Analyze the success of risk strategies using advanced approaches such as statistical hypothesis testing, causal inference, A/B testing, and uplift testing.
• Create self‑serve data products and dashboards about the merchant risk programme while ensuring data reliability and accuracy.
• Contribute to the merchant risk analytics space by helping to define the right data to be collected, collaborating with the data engineering & modeling team to ensure data pipelines and models are working smoothly, and assisting in creating documentation.
• Communicate effectively to a mixture of technical and non‑technical stakeholders of varying seniority.
• Tell a story with the data and ensure key points and recommendations are understood.
• Depending on your skillset, either incorporate machine learning techniques (e.g., predictive loss modelling) into your work analysing risk performance or collaborate with Data Scientists to achieve the same.

Qualifications

• 3+ years of experience in data analytics or machine learning, preferably in fintech or risk systems.
• Degree‑educated in Data Science/Mathematics/Engineering or a similar quantitative related degree.
• Good statistical knowledge such as causal inference, hypothesis testing, and statistical significance.
• Advanced SQL & Python skills, experienced user of BI and visualization tools such as Power BI.
• Able to deconstruct and solve problems, investigate drivers, and tell the story when interpreting and presenting actionable data insights.
• Excellent eye for detail and ability to ensure accurate and objective analysis.
• Have a “Can do” attitude, team player, eager to learn, contribute and share knowledge.
• Knowledge of payments, e‑commerce, and gambling markets desirable.
• Experience working with Snowflake and/or AWS Sagemaker.
• Experience with model implementation and optimisation.

Benefits

• Opportunity to work abroad for up to 2 weeks in the year from any location (subject to business approval).
• Flexible work – we support working from home combined with office collaboration days.
• Multiple career progression opportunities in a dynamic in‑house business.
• Discounts on fitness memberships.
• 4 paid charity days per year through the Paysafe Giving initiative on the Benevity platform.
• Paysafe holiday days for continuous service.
• Employee Network groups that foster inclusion and collaboration.

Paysafe is an equal opportunity employer. We value diversity and are committed to providing a work environment of mutual respect to everyone without regard to race, color, religion, national origin, age, gender identity or expression, or any other characteristic protected by applicable laws, regulations and ordinances.