Data Scientist (High Salary)...

Tekaris GmbH
Bristol
4 days ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Work Preference Option(s): Hybrid model Welcome to an
exciting opportunity where ambitious individuals are invited to
join a team of inquisitive minds and supportive peers, all driven
by a shared passion and diverse skills aimed at creating value for
businesses through data. About Us We are Ascent! and we help our
customers solve problems, elevate, and do existing things better.
We are on a mission to help our customers connect data, software,
and purpose to create extraordinary outcomes. We are a digital
transformation business. We specialize in software product
development, analytics, data science, IoT solutions, machine
learning, DevOps optimization, and modernization of applications,
data, and platforms. We work with incredible clients across various
industries such as smart home devices, space exploration, beer
manufacturing, finance, ecology, and logistics. We collaborate with
some of the brightest minds in successful businesses and employ
talented professionals ourselves! At Ascent, we foster a vibrant
office community where collaboration thrives and connections
flourish. Our hybrid approach emphasizes hiring individuals near
our central offices in Bristol and London to facilitate easy access
and a positive environment. We also welcome applicants from all
over the UK, valuing diversity and unique perspectives. As part of
our team, you'll be tasked with: You will work in a fast-paced,
innovation-driven data science team across various industries and
use cases. Your first project will focus on R package validation
for a global biopharma client, collaborating with validation leads
and statisticians to: - Perform package assessments - Review
business user R package assessments - Support custom package
developers to ensure compliance with standards - Release package
updates following internal/external standards Qualifications -
Thorough knowledge of R language - Experience with GitHub,
including version control, collaboration, testing, and CI/CD -
Proven track record of publishing high-quality R packages on CRAN -
Excellent written and verbal communication skills, with the ability
to explain complex technical and statistical ideas to
non-specialists Preferred Qualifications - Experience in
biostatistics and clinical programming - Familiarity with Cloud
infrastructure and services (e.g., Azure) - Background in data
science, including machine learning and Shiny app development
Working at Ascent We promote a healthy work-life balance with
flexible work arrangements. We support well-being through access to
Well Being Coaches. Your development is important to us. We offer
training, certification, regular feedback, and review to support
your growth. Our workplace is modern, supportive, and aligned with
our values of Empathy, Energy, and Audacity. We also provide
benefits tailored to each country. Ascent is an equal opportunities
employer. We actively promote inclusion and belonging. We do not
discriminate based on gender, pregnancy, maternity, marital or
civil partnership status, sexual orientation, race, ethnicity, age,
religion, disability, or other protected characteristics. Please
inform us of any reasonable accommodations needed during the
application process. If you have questions, contact our Talent
Acquisition team at . Learn more about life at
Ascent on our Life Page. #J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Best UK Universities for Machine Learning Degrees (2025 Guide)

Explore ten UK universities that deliver world-class machine-learning degrees in 2025. Compare entry requirements, course content, research strength and industry links to find the programme that fits your goals. Machine learning (ML) has shifted from academic curiosity to the engine powering everything from personalised medicine to autonomous vehicles. UK universities have long been pioneers in the field, and their programmes now blend rigorous theory with hands-on practice on industrial-scale datasets. Below, we highlight ten institutions whose undergraduate or postgraduate pathways focus squarely on machine learning. League tables move each year, but these universities consistently excel in teaching, research and collaboration with industry.

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.