Mid- to Senior-Level Data Scientist, Payment Transactions Data (вакансія неактивна)

Our team (part of the Payment’s Lab consulting company payments-lab.com), working on EagleSense (eaglesense.ai) — an ML-driven solution that helps fight first-party fraud, is looking for a Mid- to Senior- level data scientist with experience in working with payment transaction, product usage and user profile data.

About the Role: We’re seeking a Mid- to Senior-Level Data Scientist with experience in working with and building models using financial systems data (payment transactions, user profiles, user behaviour, product usage data) who will be responsible for designing, developing, and deploying models in production, that can scale efficiently. You will work closely with a team of engineers, product stakeholders and data scientists.

The candidate should have experience in developing such solutions, natural curiosity and a creative mind. The candidate should clearly understand available tools to solve relevant business problems, what data might be available and has to be used, potential solution limitations and scaling abilities.

Its integral that the candidate has a clear understanding of how an ML- and data-driven solution should work in production, and what steps can be taken to improve performance.

Responsibilities:

• Analyze large and complex datasets from various financial systems and sources to identify trends, patterns, and insights that inform product development.
• Design and develop machine learning and/or regression models to predict user behaviour, detect anomalies, optimize product usage, and enhance user profiles.
• Find opportunities to standardise features across multiple data sources and logical interpretations of patterns that help boost model performance.
• Work closely with product and engineering teams to implement models into scalable, production-ready solutions.
• Develop metrics and monitoring systems to evaluate the performance of deployed models and ensure they meet the required standards.
• Collaborate with cross-functional teams, including product managers, engineers, and other data scientists, to align data science initiatives with business goals.

Qualifications:

• Education: Degree in Data Science, Computer Science, Statistics, Mathematics, or other technical field.
• Experience: 2+ years of experience in data science roles, with a focus on financial transactions data such as banking, merchant, or payment systems.
• Technical Skills:
• Proficiency in programming languages such as Python (must have), R, or Scala.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong skills in SQL and data manipulation.
• Domain Knowledge: Understanding of financial systems data, including payment transactions, user profiles, user behavior, and product usage.
• Problem-Solving: Strong analytical and problem-solving skills, with the ability to work on complex problems and deliver solutions.
• Seniority: For this role, we’re looking for an individual that can envision how the models will be used withing the end product production, with multiple data sources. The successful candidate should also be able to find opportunities to improve model performances while standardising features across multiple data sources.
• Communication: Excellent verbal and written communication skills in English (B2+), with the ability to convey complex technical concepts to non-technical stakeholders.
• Team Player: Ability to work effectively in a collaborative, fast-paced environment.

More details about the role:

• Depending on your experience and preferences, we might start our cooperation in a consulting or part-time format that will evolve into full-time work within our team, after you demonstrate your expertise.
• It’s a contract-based position.
• Competitive and transparent compensation
• Work with professionals, clients and products in global markets
• Fully remote work with flexible working hours (mostely western european timezone)
• Professional development opportunities and a supportive work environment.