Data Analyst - Remote UK

Seekup Strategies
Havant
1 year ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Our client: They are a dynamic start-up specializing in B2B social media advocacy. They support B2B organizations frustrated with outbound sales and marketing tactics that yield little or no return. Their mission is to put people in front of logos by empowering employees to become digital brand ambassadors. By connecting marketing, Social Selling, and Employee Advocacy, they help customers build an expert brand voice, achieve higher conversion rates, and drive revenue growth.

The Role: The Data Analyst works with internal teams and client stakeholders to help drive business outcomes with data. This role is critical to our client’s ambition to be a data and insight-led boutique consultancy. The ideal candidate brings a balance of technical expertise, analytical thinking, and storytelling abilities. This role involves analyzing data, building compelling visualizations, and occasionally presenting actionable insights to clients. They are seeking a detail-oriented self-starter who is passionate about making data meaningful and impactful in driving positive business outcomes. Experience in an agency or consultancy is a plus.

Key Responsibilities:
•Data Analysis Manipulation: Collect, clean, and analyze data to uncover trends, patterns, and insights that help shape client strategies and measure program impact.
•Data Visualization Reporting: Create and maintain interactive dashboards and reports using tools like Tableau, Power BI, or Python, presenting complex data in accessible, visually compelling ways.
•Statistical Analysis Modeling: Conduct hypothesis testing, regression analysis, and other statistical techniques to validate data quality and provide actionable insights.
•Database Management: Extract, transform, and load (ETL) data from various sources, including relational databases, ensuring data integrity and accuracy.
•Collaborate with Client Teams: Work directly with internal teams and clients to understand their business goals, translating them into data-driven projects and solutions.
•Data Storytelling Presentation: Synthesize findings into cohesive stories, making complex data insights understandable for non-technical audiences.

General Duties:
•Be prepared to travel, both nationally and internationally, in accordance with our client’s travel and subsistence policy.
•Provide and utilize your own laptop, phone, and tablet to manage all work requirements and client account workloads.
•Ensure any privately-owned devices used for work adhere to GDPR, legal requirements, and relevant company policies.
•Actively participate in and contribute to industry conversations, engaging in dialogues, answering questions where appropriate, and developing trusted advisor relationships.
•Maintain confidentiality in all matters relating to the organization.

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.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.