Data Scientist

Job description

About ArborKnot:

ArborKnot is a dynamic global financial group specializing in pricing & managing distressed consumer receivables in an amicable way. With $765 million AUM (as at end May 25’), our mission is to alleviate the burden of debt on individuals, enabling them to lead better lives through innovative & data driven recovery practices.

We’re challenging traditional market practices. Our innovative approach fosters a dynamic marketplace for our clients and consumers.

With offices in Sydney, Berlin, New York, and an innovation lab in Tel Aviv, Israel, ArborKnot offers a unique opportunity to be part of a fast-growing, multicultural team dedicated to driving positive industry and social change.

Job summary

As a Data Scientist at ArborKnot, you will be at the forefront of transforming the debt recovery landscape through data. You’ll develop machine learning models that drive real-world financial decisions, working with highly imbalanced datasets and complex behavioral signals to predict repayment likelihood, detect anomalies, and optimize recovery strategies.

Your day-to-day will involve more than just model building - you'll dig deep into raw data, identify domain-specific effects, account for observational phenomena, and surface the most meaningful drivers of payments behavior. You’ll play a central role in enabling data-driven decision making across the organization, from risk assessment and pricing to portfolio allocation, performance and business strategy.

Responsibilities

• Develop, validate, optimize, and deploy ML models aligned with business goals. : Creating ML statistical models, validating their accuracy and relevance, explaining models in business terms, deploying models in production environments, and performing post-implementation validation.
• Maintain and develop model lifecycle - feature engineering, research, implementation, model explainability, and continuous monitoring.
• Collaborate with analysts, portfolio managers and other stakeholders to integrate features and requirements to our models.
• Monitor and troubleshoot data science pipeline performance to ensure the accuracy, consistency, and performance of models.
• Bring statistical theoretical knowledge into practice by designing statistical studies ,including assessment of estimation methods, A/B testing, analysis of observational data, analysis of variance etc.

Qualifications

• Bachelor's degree (BSc) in Statistics, Computer Science, or other relevant fields.
• M.Sc. in Statistics or Computer Science - advantage
• 2+ years of experience as a Data Scientist , Machine Learning Engineer, or Statistical Researcher
• Proven experience developing, evaluating, and deploying machine learning and statistical models in production environments.
• Solid understanding of statistical methods (e.g., hypothesis testing, variance estimation, A/B testing, confidence intervals).
• Strong programming skills in Python (pandas, NumPy, scikit-learn)
• Experience with SQL and writing SQL queries

Advantages

• Practical experience handling imbalanced datasets and rare event prediction (e.g. fraud, churn, default) - big advantage.
• Experience working in FinTech, collections, or fraud/risk modeling domains
• Experience with time-series modeling, survival analysis-Advantage
• Experience with cloud platforms (Google Cloud Platform, AWS, or Azure-Advantage)
• Experience with Bigquery

Soft skills:

• Strong problem-solving skills.
• Excellent communication skills, with the ability to translate complex technical concepts for non-technical stakeholders.
• Fluent in English (written & spoken).
• Exhibits a high level of responsibility and ownership in all aspects of work.

At ArborKnot, you will be at the forefront of financial innovation, working in a true multicultural environment that values creativity, collaboration, and growth. We value diversity and strive to create an inclusive work environment where employees can bring their whole self to the workplace.

If you are a highly motivated and analytical individual with a passion for data and finance, we would love to hear from you. Join us to shape the future and develop new markets.

To apply online please click the “Apply” button below or email careers@arborknot.io At ArborKnot we value diversity and strive to create an inclusive work environment where employees can bring their whole self to the workplace.