Paysafe Limited ("Paysafe") (NYSE: PSFE) (PSFE.WS) is a leading payments platform with an extensive track record of serving merchants and consumers in the global entertainment sectors. Its core purpose is to enable businesses and consumers to connect and transact seamlessly through industry-leading capabilities in payment processing, digital wallet, and online cash solutions. With over 25 years of online payment experience, an annualized transactional volume of $140 billion in 2023, and approximately 3,200 employees located in 12+ countries, Paysafe connects businesses and consumers across 260 payment types in over 40 currencies around the world. Delivered through an integrated platform, Paysafe solutions are geared toward mobile-initiated transactions, real-time analytics and the convergence between brick-and-mortar and online payments.
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Further information is available at www.paysafe.com.
We are currently looking for a hands-on Business Analytics and Data Science practitioner to lead co-lead a globally distributed team of ~100 data engineers, analysts, and data scientists to accelerate our data driven decision-making process end to end from business analysis, idealization, exploratory analysis, machine learning model building, scale and production of MLOps / LLMOps, to automation of actionable insights for sales, risk management, financial crime analysis, pricing and finance and senior executives.
What you will do:
- Learn business processes and products and gain deep understanding of their data requirements to design and apply advanced analytics solutions to optimize them.
- Design, develop, evaluate, and deploy predictive modeling, machine learning (ML), advanced analytics solutions
- Senior level data visualization to summarize and present key insights to both technical and non-technical audiences including presenting predictions and other analytical outcomes, to senior executives up to board members.
- Partner closely with other machine learning engineers to support development, experimentation, continuous integration, continuous delivery, validation, and monitoring of AI/ML Models
- Work cross-functionally with resources such as business SMEs, analysts, data engineers, architects, DBAs, infrastructure to design and deliver advanced analytic solutions
- Collect, clean, and transform large datasets from various sources for analysis.
- Apply data mining techniques to discover patterns, trends, and insights.
- Conduct exploratory data analysis to identify data quality issues or anomalies.
- Tune production models and contribute to data engineering, pipelines and MLOps etc architecturally and operationally.
To be successful you need to have:
- Minimum 5 years of experience with utilizing machine learning to optimize business outcomes including machine learning methods, design, build, testing, and implementation, generating continuous actionable insights for business stakeholders
- Minimum 3 years of experience working with Database Management Systems, Data Lake, and cloud-based ML Ecosystems such as Spark or Azure Databricks
- Deep understanding and experience with advanced statistics and modern machine learning predictive techniques, including GLMs, decision trees, forests, boosted ensembles, neural networks, deep learning, and graph analytics
- Expert knowledge of SQL
- Expert knowledge and application of modern data science languages such as Python, R, Scala, etc; in particular, serve as a subject matter expert in Python programming and the standard data science Python stack (Pandas, NumPy, Scikit-learn, XGBoost, GPGPU/Cuda, Tensorflow etc deep learning tools)
- Experience using Visual Studio Code, JetBrains Integrated Development Environments, and Vim / Jupyter, git etc
- Skilled in data modeling for advanced analytics
- Deep understanding of common design patterns and their uses
- Using work management tools such as Jira, Confluence or Azure DevOps and CI/CD tools
- Experience with real-time streaming processing technologies (e.g., Apache Flink) will be considered a big plus.
- Strong interpersonal communication and presentation skills
- Collaborative and team-centric
We offer in return:
- The opportunity to write the history of a leading and growing multinational company
- Tailor-made training and ongoing development to help you enhance your skills in the field of online payments
- Multiple career progression opportunities in a dynamic in-house business
- Environment where product expertise, professional and personal commitment are rewarded
- Competitive remuneration and social benefits package (25 days annual paid leave, health insurance, sports card, team events, company discounts, variety of soft skills, business and technical training programs)
- Fun and collaborative working atmosphere
- Flexible working model - we encourage our employees to embrace our flexible working approach. You will be expected to work from home and spend an average of three days a week at our Sofia office as part of our hybrid work model.
Are you ready to take your career to the next level? Join our team that is inspired by a unified vision and propelled by passion.
Send your CV in English.
Only shortlisted candidates will be contacted for an interview.
Wondering how our interview process looks like now? Learn more here: https://bit.ly/paysafeinterviews
Equal Employment Opportunity
Paysafe provides equal employment opportunities to all employees, and applicants for employment, and prohibits discrimination of any type with regard to ethnicity, religion, age, sex, national origin, disability status, sexual orientation, gender identity or expression, or any other protected characteristics. This policy applies to all terms and conditions of recruitment and employment. If you need any reasonable adjustments, please let us know. We will be happy to help and look forward to hearing from you.