Data Scientist

• Turn data into information, information into insight and insight into business decisions. The role of the data scientist is to deliver value, measurable insights to the wider business through the use of various statistical tools and techniques on top of a variety of data sources both internal and external to the business
• There is an element of helping to establish the team inside the business for example how it operates and engages with the business, its processes, how its measured etc so will require an element of being able to operate in a changing environment with ambiguity and being a self-starter seeking out ways to add value
• Identifying business needs and apply right approach as solution. Those solutions include train machine learning algorithms to learn about data sets and then look for patterns, anomalies or insights that can be used to build analytical models. Skilled in the supervised, unsupervised and reinforcement learning methods used in machine learning.
• With skill sets in deep learning, a more advanced method that uses neural networks to create complex analytical models.
• Experience in AI technologies will be used for some future company business needs
• Proactively identify areas to add value to the value to the business as well as fulfil the demand coming from the business
• Interpret data, analyse results using statistical techniques and provide ongoing insights to the wider business
• Being able to use data to make predictions and model different scenarios and outcomes is a central part of data science
• Work with the Data Engineers to develop and implement databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality
• Work with the data governance team to help drive consistency in MDM, Data Definitions etc to create a trusted source of data
• Acquire data from primary or secondary data sources and maintain databases/data systems
• Identify, analyze, and interpret trends or patterns in complex data sets
• Filter and “clean” data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems
• Work with management to prioritize business and information needs
• Locate and define new process improvement opportunities

Experience:
 

• Proven working experience of providing valuable insights as a data analyst or data scientist.
• Significant experience in a similar role and industry.

Knowledge: 
 

• Strong knowledge and experience of using analytics and reporting tools and languages especially Python, Tableau, PowerBI, SQL. NoSQL, JavaScript. 
• Knowledge and experience of Data tools and models
• Business understanding
• SAS, R
• Knowledge and experience of Data tools and models
• Knowledge of our industry and markets

Skills:

• Technical expertise regarding data models, database design, data manipulation, data mining and segmentation techniques
• Strong analytics skills with the ability to collect, organise, analyse and disseminate significant amounts of information with attention to detail and accuracy decision trees; random forests; Naïve Bayes classifiers k-nearest neighbor; logistic regression linear regression; and k-means clustering
• AI technologies, Deep learning and machine learning
• Adept at queries, report writing and presenting findings 
• Acquisition data from primary and/or secondary sources 
• Ability to present and communicate across the business
• Experience of proactively finding areas to add value to the business as well as fulfilling existing demand

Qualifications

• Data Science, Statistics BS in Mathematics, Economics, Computer Science, Information Management.

Desirable Qualifications (Not a must)

• MSc level
• MBA