Data Analyst

iO Associates
Manchester
2 months ago
Applications closed

Related Jobs

View all jobs

Data analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Job Opportunity: Data Analyst

Location:Manchester (Hybrid)
Position Type:Full-Time
Salary:£45,000

About the Company

My client is an exciting scaling eCommerce business on a mission to revolutionise their industry by offering innovative and customer-centric solutions. They are powered by a fast-paced, dynamic team focused on delivering exceptional services and driving growth.

This is a unique opportunity to join a rapidly growing organisation, where you'll play a key role in shaping processes and driving meaningful change, all while working in a collaborative and innovative environment.

About the Role

As a Data Analyst, you will work cross-functionally across all departments to extract and surface valuable insights. Your analysis will focus on key metrics such as funnel conversions, net deposits, transfers, and client engagement. You'll have the opportunity to propose innovative solutions that directly enhance business performance and the customer experience.

Key Responsibilities:

Collect, analyse, and interpret data to identify trends, patterns, and actionable insights. Develop, monitor, and report on key performance indicators (KPIs) to measure the success of products and services. Build automated dashboards and reporting tools, particularly using ThoughtSpot, to provide stakeholders with real-time insights. Analyse client behaviour to identify pain points and develop strategies to improve retention and acquisition. Collaborate with various teams to deliver data-driven recommendations that enhance client experience and satisfaction.

What's on Offer

Hybrid working for flexibility and work-life balance. Generous holiday allowance that increases with tenure. Comprehensive health benefits. A competitive bonus scheme. An excellent pension plan. The chance to contribute to shaping the company's culture and processes.

About You

You thrive under pressure and excel at meeting deadlines while maintaining professionalism and approachability. You're a problem solver who is determined, flexible, and eager to drive impactful change.

Required Skills & Experience:

2-4 years of experience in a data analytics role, ideally within an eCommerce or client-focused digital business. Proficiency in SQL and Excel, with strong analytical and problem-solving skills. Experience with ThoughtSpot, including building automated dashboards or similar tools such as Power BI, Looker and Tableau. Passionate about data and uncovering insights to drive business improvements.

Why Join?

This is a fantastic opportunity to join a scaling business at an exciting stage in its growth journey. You'll be working in a fast-paced, KPI-driven environment that values innovation, efficiency, and collaboration.

Ready to make an impact?Apply now to learn more about how you can help drive success in this dynamic and growing eCommerce organisation.

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.

Tips for Staying Inspired: How Machine Learning Pros Fuel Creativity and Innovation

Machine learning (ML) continues to reshape industries—from personalised e-commerce recommendations and autonomous vehicles to advanced healthcare diagnostics and predictive maintenance in manufacturing. Yet behind every revolutionary model lies a challenging and sometimes repetitive process: data cleaning, hyperparameter tuning, infrastructure management, stakeholder communications, and constant performance monitoring. It’s no wonder many ML professionals can experience creative fatigue or get stuck in the daily grind. So, how do machine learning experts keep their spark alive and continually generate fresh ideas? Below, you’ll find ten actionable strategies that successful ML engineers, data scientists, and research scientists use to stay innovative and push boundaries. Whether you’re an experienced practitioner or just breaking into the field, these tips can help you fuel creativity and discover new angles for solving complex problems.

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.