Data Scientist

JAM IT Consultancy Ltd; England; Hybrid; GBP 45,000 - 60,000; Full time

Job summary

A tech consultancy firm in the United Kingdom is looking for a Data Scientist to develop sophisticated algorithms and predictive models. The ideal candidate will have a strong mathematical and statistical background, experience in Python and R, and the ability to integrate models into software applications. This role requires commuting to the office 3-4 days a week as per the hybrid policy. Join a collaborative team to create impactful software solutions.

Qualifications

• Strong mathematical and statistical background.
• Demonstrable experience in data science and predictive model development.
• Experience working within an agile environment.

Responsibilities

• Develop predictive models using statistical techniques.
• Integrate algorithms and code into products.
• Conduct research and develop prototypes.

Skills

Python

R

Statistical analysis

Machine learning

Data visualization

Agile methodologies

Git

Education

Bachelor's Degree in a STEM subject

Post-graduate degree in Data Science or related field

Tools

Numpy

Pandas

Pytorch

Scikit-learn

Docker

Kubernetes

Microsoft SQL Server

Job description

As a Data Scientist, you will develop sophisticated algorithms and predictive models, leveraging a broad spectrum of techniques from mathematical and statistical methods to advanced machine learning approaches. You will be working alongside DevOps and software development teams to ensure seamless integration and efficacy of your models to our clients software to deliver mission-critical communications solutions for customers.

This is an office-based vacancy and as such we expect all applicants to be willing to commute to our offices a minimum of 3-4 days per week as per our hybrid working policy.

Key Responsibilities

• Data Science & Software Development
• Craft and refine predictive models using a diverse array of methods, including but not limited to linear programming, heuristic algorithms, and machine learning techniques.
• Solve complex problems using statistical techniques and data analysis.
• Stay abreast of current research and integrate relevant findings into your work.
• Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods.
• Develop algorithms and code, primarily using Python and R, and integrate these into our products.
• Conduct research to develop prototypes and proof of concepts.
• Work within an agile team to develop applications to meet product/customer requirements.
• Thoroughly test algorithms or developments to make sure they perform the desired task correctly in all cases.
• Work with Quality Assurance teams/processes to validate builds ready for launch.

Maintenance & improvement

• Problem solve and fix bugs as discovered/reported.
• Address and resolve any issues that arise post-deployment.
• Perform ongoing maintenance or upgrade of the platform as required, following internal change procedures at all times.
• Share ideas and work on projects for improving applications, process or the wider platform.
• Review projects/deployments and learn lessons to improve future performance.
• Stay up to date with data science literature and technological advancements. Learn and test new technologies, frameworks, research paper and languages as relevant.

About You

• Bachelor’s Degree in a STEM subject, preferably from a Russell Group University.
• Strong mathematical and statistical background; expertise in Python and R, including libraries like Numpy, Pandas, Pytorch and Scikit-learn.
• Demonstrable experience in data science and a proven track record in developing predictive models.
• Experience contributing to a software project / product.
• Experience with databases.
• A post-graduate degree in Data Science or a related field
• Experience with source control, in particular Git.
• Experience working within an agile environment, in particular Scrum, and applying supporting practices.
• Experience with C# and Microsoft SQL Server.
• Good experience in database technologies, such as Microsoft SQL Server.
• Experience in developing containerising applications with Docker and using orchestration such as Kubernetes.