This role provides the link between the pure commercial business needs with the analytical engines, creating the link between business areas and a team of data scientists. Marketing campaigns, customer intelligence, churn reduction, product definition and other relevant areas of the business have a clear need of data. This role will support the advance analysis of data in order to obtain business-related insights that foster the development of the data-driven business strategy of Openbank.
- This position stands within the Commercial Intelligence team, and we expect someone that knows how to optimize more than ROC-AUC curves; you have proven experience applying ML engines to improve Business areas outcomes (measured in financial gains or savings) and take data-driven decisions. In the past you have faced data-atheists and does not frustrate you to lead them in the path of data conversion.
- You know how to create metrics that measure the performance of certain customer behaviours and enjoy the experimentation of behavioural actions to analyze the evolution of the created indicators.
- You want to find the position where you can participate in the design long-term plans for data-products and strategy, although you understand business urgent requests and sometimes you just need to get the work done. You have worked on several projects at the same time and you understand how to balance delivery and progress.
- You enjoy never-faced challenges and data sources, and know how to prioritize opportunities with business needs and Directors’ requests; however our Senior Data Team consists of ex-members of the most prestigious data-companies and academic programs, and we know that success comes only through collaboration.
- Your critical scientific thinking is normally reinforced by listening to others’ opinions with respect to the best algorithmic decisions; however you easily recognize where a logistic-regression will do the job to achieve an 80% acceptable solution.
- Scalable solutions and production-readiness are two of your mantras; however, we have a ML-Operations team that will support you in achieving technical excellence.
- You are not afraid of designing an ETL for a newly introduced dataset, generating concrete specifications for its automation; despite we have a robust Data Engineering team maintaining hundreds of Scala ETLs, the seniority of this role requires being able to communicate with this highly technical team.
- Supervising other fellow data scientists is an attractive point as it can eventually help you achieve bigger more interesting initiatives. In our team, we nurture a meritocratic culture trying to provide professional development opportunities.
Experience and knowledge:
- Excellent communication skills and influence, with the ability to translate business issues into analytical solutions
- Successfully managed the end to end delivery of insights and value, including resourcing, budgeting and prioritization.
- Statistical modelling and machine learning: you know the difference of a random forest and k-means, and know how to implement them in different programming languages (ideally Python or Spark). We´ll double-check this with you!
- Dealing with large datasets, and implementing scalable solutions. You know when pandas breaks and have dealt with different distributed solutions such as dask or spark.
- How to solve problems using data: analyze the problem and decompose it into different analytical components, and recycle all the components you can from other projects.
- Software development: you know what git means, and how to develop your own code, test it and use it to produce actionable results. Open-source lovers get a plus if you show us your github!
- Data Visualization, and tools like ggplot, matplotlib, tableau, or similar. Bonus points for plotly, and standing ovation for Quicksight.
- For this level of seniority, you have experience on geo-spatial analytics, graph-theory, and natural-language processing.
- Automation Obsessed: Cloud infrastructures are your main asset in order to automate all ML-related problem so the machine does the most of the work for you, or at least you are highly interested in collaborating closely with the ML-Ops team.
- For this role you need to have at least 3 years of proven experience in an industrial environment
- University Degree: Informatics Engineering, Industrial Engineering, Telecommunications Engineering, Mathematics, Physics, Statistics.
- You need to have a high proficiency or fluency in English and Spanish.
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