Graduate Data Scientist at REPL Group

About the job

Our Data Science Practice is growing and we’re looking for Graduates passionate about all things data to join us! Our Data Science Team is part of the delivery consulting team, delivering a data science consulting offering across a wide portfolio of clients and services. As such, we are working on a broad spectrum of activities, ranging from algorithms development, data analysis, and software development support.

Throughout the Graduate Programme, you’ll be working side-by-side with clients worldwide to provide bespoke data science consultations across all areas of retail in Supply Chain, Workforce Management, and Customer Experience. You’ll have the opportunity to rotate throughout the main areas of the data program on data analysis, statistical hypothesis testing, machine learning development, and data engineering.

From day 1, you’ll be part of our supportive graduate community which offers a combination of training and development opportunities as well as graduate days and socials. Throughout the graduate consultant programme, we’ll review your progress, with regular salary increments to reflect your development and depth of experience. On successful completion, you’ll become a Senior Data Scientist with all the additional responsibility and further opportunity to learn/grow that comes hand in hand with promotion.

What are the main tasks that you’d be doing?

• Provide technical input to algorithms development and data analysis activities.

• Complete the internal education program, and be part of the weekly study groups guided by the appointed training mentor

• Work closely with external clients across the world to deliver required data analysis and machine learning models.

• Work closely with the rest of the data science team to develop a robust interface framework for our in-house platform algorithms.

• Produce technical documentation covering algorithm-related requirements, design specifications, and test specifications.

• Develop high-quality maintainable code in accordance with the current software process.

• Develop and implement test strategies to verify and validate algorithm features.

• Investigate and fix issues in new and existing software/features.

• Produce prototypes to demonstrate concepts and ideas.

• Support future software platform deployments.

• Produce/update software process documentation.

• Help establish and maintain the data science toolchain.

What we’re looking for:

• Strong data related academic background i.e. Masters level in degree in a numerate subject, preferably data science, or strong theoretical bachelors degree

• Theoretical knowledge of classical statistical methods, bayesian learning, and neural networks, and its application to machine learning techniques.

• Keen to utilise up-to-date software development practices.

• Good communications skills, verbal and written.

• Self-starter, happy to work alone or as part of a team.

• Willing to occasionally work off-site at supplier or customer sites.

• Have a passion for data, innovation, and commitment to continue to learn new approaches in data analytics, scientific thinking, machine learning, and making it happen using engineering approaches.

It would be great if you had any experience/knowledge of, or a desire to learn about:

• Scripting Python/R experience.

• Demonstrable experience with RStudio or Jupyter notebooks.

• Experience with Tensor Flow.

• Experience of Hadoop.

• Experience with high-level software languages such as Scala, Java or C#.

• Experience in working in an Agile development environment.

• Experience in utilising a continuous integration approach to software development.

• Experience with software containers e.g. Docker.

• Comfortable working with different data science tools.

REPL is an equal opportunity employer and we know the value of a diverse and inclusive workforce. We have very active communities for Women in Tech, Automation and Innovation and we are also actively involved in the local community. As such, we particularly encourage applicants from a diverse range of backgrounds.