Senior Data Scientist, Qflow

• Strong experience in a data-focused environment, with an emphasis on building scalable, high-performance predictive models
• Advanced proficiency in Python, SQL and modern machine learning frameworks
• Experience in taking machine learning models from development into production
• Familiar with fine tuning Large Language Models (LLMs) and prompt engineering
• Familiarity with SQL and noSQL databases
• Familiarity with cloud architecture, instrumentation, CI/CD, and git
• Understanding of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.)
• Demonstrated ability to identify opportunities, take initiative on improvements, and drive projects from concept to completion with minimal oversight
• Proven track record in delivering high-quality code through test-driven development, pair programming, and collaborative development practices
• Excellent communication and interpersonal skills, with demonstrated ability to convey complex technical concepts to diverse audiences and stakeholders
• Thrives in a fast-paced, ambiguous start-up environment, driving the delivery of software engineering solutions that are both innovative and tightly aligned with commercial goals

Desirable

• We’re looking for a new team member who will be responsible for leveraging data to drive business decisions. You'll be involved in the entire data science pipeline from exploration and modelling to experimentation and deployment. We need a Data Scientist who can not only develop models but also bring them into production in collaboration with the rest our Engineering team
• You’ll be working in our Engineering community within the Data Experience Team, working closely with Product and other engineers reporting to the Senior Engineering Manager
• Researching, prototyping and deploying AI/ML solutions in production
• Collaborate with stakeholders to identify and understand business needs, translating them into data-driven solutions
• Perform exploratory data analysis (EDA) to uncover trends and patterns
• Develop and apply advanced statistical and machine learning models to solve business problems, including forecasting, segmentation, optimization, and predictive modelling
• Conduct rigorous data analysis, interpret results, and communicate findings to technical and non-technical audiences in a clear and compelling manner
• Stay abreast of emerging technologies and industry best practices in data science, continuously exploring opportunities for innovation and improvement
• Contribute to the development of a data-driven culture within the organization, promoting the value of data-informed decision-making
• Champion best practice in coding, version control, documentation and automation