Data Science Technical Team Lead állás Országos

• Management of Data Science projects and services.  Including contributing expertise and business context to project planning and implementation, and oversight of the performance of Data Science models deployed in production. 
  
• Identifying new opportunities where Data Science can deliver business value, particularly through automating or enhancing account-level decision-making (e.g. bonus-abuser detection).
  
• Line-management of the Data Science team.  Including leading Data Science sprints and retrospectives, providing support and expertise to the team, and fostering a culture of continuous improvement and agile delivery.
  
• Collaborate with Data Engineering (within BI) to ensure resilient deployment of models, and smooth integration with both our technical infrastructure and operational processes across the business.
  
• Hands-on modelling work, including building prediction models to identify accounts matching certain behaviour patterns (e.g. trading and compliance risks), and content automation and personalisation models (including recommendation engines).
  

›› We are looking for someone with strong hands-on experience in Data Science, capable of both managing the team and engaging directly with technical work when needed.

• Proven experience leading Data Science teams in a commercial environment, including experience of agile environments (e.g. sprints and retrospectives) and pragmatic stakeholder management.
  
• Deep understanding of the full model lifecycle, from problem scoping and data exploration through to deployment, monitoring and iteration.  Track record of delivering robust production-ready batch- and real-time models that fulfil business goals, including operationalising them in a business setting.
  
• Thorough understanding and experience of different ML techniques, notably supervised regression and classification models (Deep NN, XGBoost, GLM), unsupervised learning methods (clustering, principal components) and reinforcement learning (actor-critical, temporal difference).  Understanding of model-selection techniques and model diagnostics.  Familiarity with modern data engineering and MLOps practices is desirable.
  
• Detailed knowledge of querying data in SQL engines (ideally in BigQuery or similar database engines) and in no-SQL engines (e.g. MongoDB and Firestore).  Including the ability to work with complex data structures and very large data volumes. 
  
• Advanced Python or R for data manipulation and machine learning.  Working knowledge of data visualisation tools.
  
• Excellent communication skills are essential, including a high level of written and spoken English.
  
  

• Full home office opportunity, if you want you can visit the office in the 13th district
  
• attractive benefits including cafeteria and private medical insurance
  
• We encourage employee development
  
• We reward initiative
  
• We deal with stress in a calm manner and keep an eye on the prize
  
• Success is contagious here and we celebrate it!
  
• We use state of the art technology
  
• We embrace IT challenges!
  
• We have an awesome multi-cultural work environment