Senior Data Analyst - Fraud Prevention

Details of the offer

Hello!
We're Teya. Teya is a payment and software service provider, headquartered in London serving small, local businesses across Europe.
Founded in 2019, we build easy to use, integrated tools that enable our members to accept payments and boost business performance.
At Teya we believe small, local businesses are the lifeblood of our communities.
We're here because we don't believe there's a level playing field that gives small businesses with a fighting chance against the giants of the high street.
We're here because we see banks and legacy service providers making things harder for them.
We don't think the best technology or the best service should be reserved for those with the biggest headquarters.
We're here to fight for a future where small, local businesses can thrive, and to commit the same dedication they offer all of us.
Become a part of our story. We're looking for exceptional talent to join our mission.
We offer a chance to create impact in a high-energy and connected culture, while benefiting from continuous learning opportunities, a supportive community which is proud to serve our mission, and comprehensive benefits.
Your Mission You will be a part of a joint team of machine learning engineers and data scientists building and evolving ML models, real time systems, reports, and deep analysis of fraud detection and mitigation activities to protect merchants, their customers, and Teya from fraudulent activities.
Working with advanced predictive models and scalable software systems, build and grow intelligent solutions to reduce all kinds of risk and allow Teya to focus on effectively serving our merchants.
Key individual contributor for a diverse and innovative team to create deep understanding of big data inputs and contribute to continuous improvement while addressing fast-moving risks and opportunities.
Working with senior product, business, and engineering leaders to analyze data, identify opportunities for building new models, build and maintain real time dashboards, and deliver insights through in-depth reports.
Collaborate with your peers across Teya to share insights and enable real-time decision making wherever opportunity arises.
As a Senior Data Analyst on the Fraud Prevention team you will:
Lead with data to design, develop, and implement solutions for Fraud Prevention;Collect, store, and analyse large data sets;Integrate data into business processes and systems;Write complex SQL queries and scripts;Collaborate with cross-functional teams, including data scientists, ML engineers, product managers, and business analysts;Build and maintain dashboards and reports in a variety of environments including Snowflake and Tableau;Effectively manage business stakeholders and drive initiatives to promote actionable insights, identifying and prioritising requirements and owning a roadmap of deliverables;Analyse external customer and internal business data working with teams across different countries to drive optimisation of our products;Build predictive models to accurately forecast our numbers and evaluate against the budget and actuals.Promote a data-driven culture across the businessYour Story Basic Requirements
3+ years of professional data analyst experience in a technical domainHighly proficient in SQL and Tableau (or equivalent BI tool)Good analytical and problem-solving skillsSelf-starter, comfortable in a fast-paced environment and able to adapt to changing circumstances quicklyCapable of translating complex data into understandable conclusions and recommendationsAbility to think creatively and insightfully about business problemsGood written and verbal communication skillsPreferred Requirements
Experience with Machine Learning and Python (time-series analysis, forecasting)Familiarity with AWS environment (SageMaker, S3, Redshift)Familiarity with SnowflakeBachelor's degree in mathematics, statistics, or relevant experience in related fieldThe Perks Health Insurance;25 days of Annual leave (+ Bank holidays);Office snacks every day;Flexible working hours, as long it suits both you and your team.
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Nominal Salary: To be agreed

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