• Design and implement data validation pipelines and model evaluation workflows in a cloud environment (AWS). • Integrate data and evaluation metrics into an automated, auditable workflow. • Modularize the pipeline to facilitate reuse, testing, and maintenance. • Collaborate with Data Science, Data Engineering, and Product teams. • Ensure best practices for versioning, logging, monitoring, and automated testing. • Propose continuous improvements to data architecture and validation processes.

Role Description We’re looking for an experienced Senior Data Scientist to help us change the way the world works, with Parallels: anytime, anywhere, any-device productivity. - Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business. - Provide insights to help business and product leaders understand marketplace dynamics, user behaviors, and long-term trends. - Produce recommendations and use statistical techniques and hypothesis testing to validate your findings. - Build, deploy and maintain models. - Ensure data quality through processing, automation, modeling, and reporting. - Contribute to the growth of knowledge of our team with internal and external documentation or presentations. Qualifications - MS or PhD in Math, Physics, Statistics, Economics, Computer Science, or similar domain. - 5+ years of experience in data science or equivalent role. - Experience working with funnel optimization, user segmentation, cohort analyses, time series analyses, regression models, etc. - Expertise with A/B Testing, and statistical analysis in Python. - Proficiency in one or more data visualization tools (e.g., Tableau, Looker, PowerBI). - The insight to take ambiguous problems and solve them in a structured, hypothesis-driven, data-supported way. Benefits - Fully remote workspace. - No pressure to work in an office whatsoever. - Flexible hours. - A growing team with a ton of energy and smart, motivated, fun people. Company Description Parallels is a top VDI/EUC product helping businesses since 1999. Whether it’s desktop or cloud, on-prem or hybrid, Parallels has a solution to help your company optimize the speed and security of your work environment at an affordable price.

• Building and refining credit scoring models that assess customer creditworthiness, default risk, and loan pricing across multiple markets • Developing and testing ML models for loan eligibility and pricing optimisation through A/B testing and statistical analysis • Continuously improving eligibility criteria by analysing repayment data, engineering new features, and monitoring credit performance for risk shifts and margin impact • Collaborating cross-functionally with engineers, data scientists, and commercial stakeholders to scale models into production

• Building and refining credit scoring models that assess customer creditworthiness, default risk, and loan pricing across multiple markets • Developing and testing ML models for loan eligibility and pricing optimisation through A/B testing and statistical analysis • Continuously improving eligibility criteria by analysing repayment data, engineering new features, and monitoring credit performance for risk shifts and margin impact • Collaborating cross-functionally with engineers, data scientists, and commercial stakeholders to scale models into production