Senior Analytics Manager - SAS / SQL / Python / R
You'll play a key role in the decision making to drive an analytics change agenda, delivering against the analytics roadmap for long term growth.
- Build highly effective relationships with business stakeholders, manage expectations and increase team visibility around projects delivered.
- Liaise with other centres of expertise around the group to share best practice and participates in setting direction
- Use internal and external data sources to better understand customers and the wider external market. Also consistently improve the data quality and richness.
- Act as a subject matter expert on external customer and prospect data available including liaison with external providers. Provide internal guidance and expertise to the Analytics team in relation to external data to ensure all team members take an efficient and consistent approach towards the use of external data.
- Act as a subject matter expert on internal systems and how they interrelate and feed into the data available to the Analytics teams.
- Oversee the periodic evaluation of existing data management processes and procedures and suggest improvements where appropriate. Support the reduction of data stored externally and/or redundantly in environments other than an enterprise repository.
- Guide & implement the group information security policy within the team and ensure all information security guidelines are adhered to.
- Strong statistics/machine learning experience (using R or Python) and highly proficient in SAS / SQL
- BSc or MSc in Machine Learning, Statistics, Computer Science, Artificial Intelligence or Mathematics
- Experience of working with large volumes of data
- Strong technical work experience with big data technologies ie Hadoop & visualisation tools such as Qlikview, Tableau
- Have directly relevant experience within financial services or an alternative data driven organization
- Have directly used visualisation tools, delivered Self Serve Analytics
- Implemented data related solutions based upon leading practices in data warehousing, business intelligence, analytics, data governance and information security
- Worked with structured and unstructured data and relational database tools, theories and techniques
- Deep understanding of the principles of data management and information security.