Data Scientist

Exponential Science Ltd
London
10 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Consumer Lending Data Scientist

Data Scientist - Imaging - Remote - Outside IR35

Data Scientist (Predictive Modelling) – NHS

Data Scientist - New

Exponential Science is a foundation led by visionary founders Dr. Paolo Tasca and Nikhil Vadgama, who have advanced emerging technologies through education, research, and innovation. Recognising the power of the convergence of technologies such as blockchain, AI, and IoT to tackle complex multidisciplinary challenges, they founded Exponential Science as a natural evolution of their long-standing work, aiming to strive towards a more inclusive and innovative future for all.

Role and responsibilities

Exponential Science is looking fordata scientistwho can:

  • Gather, review and summarise academic literature related to the research topic of interest
  • Develop methodologies for creating scientific measures across the cryptocurrency and blockchain ecosystem
  • Collect and process data and information related to the research topic of interest
  • Write blog posts on research studies conducted by members from the Foundation
  • Perform peer review and draft reviewer’s report
  • Participate in research seminars
  • Participate in research projects focusing on quantitative indicators among cryptocurrency communities and other DLT related subjects
  • Develop ML/NLP methods to be used to extract and process information in the context of DLT
  • Develop code, tools, and methodologies with regards to the cryptocurrency related projects

Skill requirements

The ideal candidates are expected to have the following qualities:

  • Prior research and development experience
  • Good comprehension and abstraction skills
  • Grit and persistence
  • Reliability
  • Knowledge of statistics, time series analysis, and network theory is beneficial
  • Genuine interest in research on DLT and experience working with Big Data
  • Experience with AWS (desirable)

The position is suitable for candidates looking to get more experience in the field of research and development of innovative methods in deep tech. The ideal candidate is characterised by a strong knowledge of and passion for the blockchain and technology industry.


Location: London, England / Hybrid

Exponential Science is an equal opportunity employer.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.