Short Description
Working collaboratively with product owners across the organisation to deliver the insights to market facing products and segments of our customer base.Job Description
- Proficiency in English language, verbal and written
- Significant experience of applying big data, machine learning, and AI technologies to solve data oriented problems
- Analytics, modelling or software development experience including coding/software development skills
- Experience of R, Python or Java including the key numerical, analytical and machine learning libraries
- A self-starter who loves to explore, define and deliver
- Apache Spark, Hadoop and other available ML services like AWS, Azure, Google big data solutions
- Good working knowledge of SQL, data warehousing & NoSQL databases
- A Masters level degree in a quantitative discipline such as mathematics, Finance, physics, computer science, data science or engineering.
- Key accountabilities and decision ownership: (8 or 10 max)
- Drive the exploration & definition of what a financial metrics focusses peer bench mark solution should contain and deliver on the analytics to actually deliver these.
- Determine & define and most relevant metrics relating to the financial health of our customers
- Use available customer data to analyse the importance of metrics and how they relate. Based on this create working calculations, segmentations and insights.
- Work in close co-operation with the Compass product engineering teams to productize the analytics into dashboards and insights.
- Support the development of associated roadmaps and product business cases when relevant with clearly defined outcome/expected results
- Working collaboratively with product owners across the organisation to deliver the insights to market facing products and segments of our customer base.
- Must have: (5 or 6 Max)
- Analytics, modelling or diligence experience gained in consulting or finance related sector, preferably in the SMB space
- Significant experience of applying big data, machine learning, and broad analytics technologies to solve business focussed problems
- Strong demonstrated capability to translate data into relevant business insights
- Expert knowledge of a scientific computing language such as R or Python including the key numerical, analytical and machine learning libraries
- A curious mind & intrinsic motivation to explore, define and deliver
- Proactive in attending ML/AI meet ups.
- Preferred: (2 or 3 Max)
- Background with accounting & benchmarking
- Apache Spark, Hadoop and other available ML services like AWS, Azure, Google big data solutions
- Good Knowledge of Excel & Powerpoint
- Good working knowledge of SQL, data warehousing & NoSQL databases
Data Scientist