Founding Data Engineer

Go Places
London
1 month ago
Applications closed

Related Jobs

View all jobs

Founding ML Engineer

Senior Backend Engineer (Python) - 6 month contract

Principal Data Engineer - Core Systems

Full Stack Data Engineer

Data Engineer

Senior Data Scientist

Position overview:

We are seeking an experienced and innovative data engineer to be the first hire on our data team. This is an exciting opportunity to build our data capabilities from the ground up. As the first Data engineer, you will be responsible for shaping the data strategy, designing the data architecture, and driving data-driven decision-making for the company. You will work closely with the business founders, Product and Operations function, leveraging your expertise in data analysis, machine learning, and statistics to unlock the potential of our data.


Company overview:

At Go Places, we're not just simplifying the world of Social Commerce – we're revolutionising it, reshaping how brands thrive in the era of socially enabled transactions. We've curated a portfolio of exceptional brands, unlocking their potential for Social Commerce revenue growth. We provide an end-to-end solution that sees us manage everything from logistics and forecasting to affiliate management and Live Shopping. With a blend of unparalleled experience, expertise, and state-of-the-art technology, we're changing the way brands think about the highest growth channel in E-commerce.


Unique responsibility:

  • Design, build and maintain the unique data model (deep learning model) for analysing and predicting shopping behaviour on social medias (like TikTok)
  • Iteratively and long term improve accuracy of this model in order to have the best predictive model for social commerce in the world


Key Responsibilities:

  • Support the ongoing development of our data governance, BI tools and technologies
  • Analyse large datasets to extract actionable insights, trends, and patterns
  • Design, implement, and optimise machine learning models to solve business problems
  • Develop and maintain data pipelines, ensuring data integrity and quality
  • Collaborate with stakeholders to understand business objectives and translate them into data science projects
  • Collaborate with developers to define what data we need to gather and how
  • Perform statistical analyses and hypothesis testing to validate findings
  • Create data visualisations, dashboards, and reports to communicate findings effectively
  • Stay current with industry trends, tools, and techniques in data science and machine learning


Requirements:

  • Bachelor’s degree in Computer Science, Mathematics, Statistics or other relevant field
  • Strong skills in statistical analysis and machine learning
  • Proficiency in Python, R, SQL, and data manipulation tools
  • Experience with data visualisation tools such as Quicksight, Tableau, Apache Superset or Power BI
  • Demonstrated leadership and self-direction. Willingness to both teach others and learn new techniques
  • Comfortable working in a fast paced, ambiguous and high growth environment
  • Willingness to explore, test and use the latest AI improvements and models. Introduce them then in the company in order to increase the performance


What We Offer:

  • Competitive salary and benefits package.
  • 25 days holiday + your birthday off
  • Opportunity to work with cutting-edge technology and be the Founding member of the Data Science team.
  • A creative and collaborative work environment.
  • Significant impact on the company’s data and technology direction
  • The chance to work at an early-stage, fast growing start-up backed by some of Europe’s leading Venture Capital funds
  • The chance to grow with the company and to build and manage a larger data team in the future
  • Flexible working arrangements (3 days a week in our London office)

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 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.