Data Science Engineer
Salary : As Per Industry Standards.
Job Views: 123
• Consulting with internal clients on how data can be optimised with further data / analytics, and
recommending creative ways it can drive genuine value to the business.
• Building analytics models using a range of data science approaches, such as Machine
Learning (e.g. Random Forests & XGBoost), Statistical techniques (e.g. A/B testing, sig-
testing, ANOVA, correlation etc), along with wider analytical approaches such as Time Series &
analytics with unstructured data – e.g. Natural language processing.
• Conducting analytics on market research data, such as Segmentation (Factor Analysis and
Cluster Analysis), and key driver analysis (e.g. Correlations and Multinomial Logistic
• Ensuring consistent, accurate and quality analysis is delivered; managing development tasks
to create new products for the group; ensuring projects are delivered in a timely, profitable and
• Working with the UK office on a number of projects simultaneously, with different teams and
levels of complexity
• Synthesising and communicating information and models in a clear, compelling and
• Ensuring our offer is kept up-to-date by appraising new techniques and models, and
discussing with internal colleagues.
• Ensuring compliance with GDPR and other data privacy and protection regulations, by liaising
with management and IT.
Recruiter: Disha Chauhan
Created Date: 18-12-2019
Experience Requirements: Commercial skills• An ability to communicate clearly to internal clients, discussing and advising on businessobjectives• Proven track record of how results can be deployed within businesses• To take a flexible approach to workload, to work autonomously when required, demonstratingthe ability to prioritise and organise and remain calm under pressure• Continuous improvement – in a fast-moving field, the desire to stay on top of new techniquesand tools is essentialTechnical / Advanced Analytics skills• Must demonstrate a strong working knowledge of advanced analytical techniques, such asregression, segmentation, machine learning, natural language processing, text analytics, andtime-series modelling• Experience of a wide variety of technologies including: R and/or Python, and SQL. A workingknowledge of Hadoop, Spark or similar would be beneficial.• Understanding and experience with cloud infrastructures such as AWS and how to integrateR/Python analytical workflows would be highly desirable.• Proven track record with accessing and manipulating client customer databases / data lakes,and web scraping tools and techniques.Software skills• Analytics: R or Python programming with SQL for data manipulation• Should be a strong user of MS Excel, and MS PowerPoint• Will require strong SPSS skills using Syntax
Salary Range: As Per Industry Standards.