Senior Data Scientist

Accountabilities

• Develop and maintain models for fraud detection, image validation, recommendations and other ML use cases, both batch and real time
• Discover and prioritise new use cases for data science techniques across Fresha’s product and workflows
• Prioritise your roadmap for maximum impact across different functions
• Mentor and coach an existing team of junior data scientists
• Collaborate closely with product, engineering, marketing and commercial teams to bring data science techniques to life


You’ll also work with the rest of the analytics team to find robust data sources and leverage existing capabilities, then develop new architectures only where needed.

Key skills

• Technical Skills: You should be highly proficient with programming languages such as Python/ R and SQL. You should also have extensive experience with data mining, mathematics, and statistical analysis, with the capability to derive actionable insights from complex data sets.
• ML: You should have demonstrable experience applying data science methods to real-world data problems, particularly in building, deploying, and optimising machine learning models across a variety of projects.
• Commercial: You need a strong understanding of how data science fits into the wider business context, with the ability to use data insights to influence commercial strategies and decision-making. Your insights should be directly tied to improving business KPIs with ML models.
• Communication: Exceptional communication skills are needed. You should be comfortable explaining complex data insights in simple terms and persuasively communicating your findings to influence strategic decisions.
• Motivation: The ideal candidate is ambitious, determined, and self-motivated, able to navigate the fast-paced and dynamic environment at Fresha. Your ability to stay motivated, navigate challenges, and drive forward our analytics offering will be crucial for your success
• Preferred but not required: Familiarity with dbt and other data analysis tools would be a bonus

Bonus points:

• Experience using cloud notebooks and AWS containerisation
• Experience with Streamlit 
• Experience working in fast-paced scale ups