Data Analyst

HICX
Manchester
7 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

HICX is a leading worldwide provider of enterprise SaaS solutions for digital supplier management. Learn more about HICX We are looking for a Data Analyst to join our fast-growing Implementation Team. The role will give you a lot of exposure and interaction directly with the customer, build up know-how around Enterprise systems and integrations. You will work with some of the world’s leading organisations (EDF Energy, BAE Systems, Novartis, Mondelez, etc.) with HICX on some of the most challenging projects. Responsibilities Collect, clean, and analyze data from various sources using SQL, Java, Python, and other tools Create and maintain ETL scripts to handle data transformations for data migration and integration Develop and maintain data models, dashboards, and reports to communicate insights to stakeholders Prepare customized reports and dashboards using analytical tools to facilitate effective decision making Work with cross-functional teams to identify areas for improvement and develop recommendations based on data analysis Collaborate with other team members to ensure data accuracy and consistency across various systems and tools Engage in application surveillance and monitoring and reacting appropriately under SLAs Assist with ad-hoc data analysis requests as needed by the business Requirements Essential: 2 years experience in a data analysis role in Procurement, Supply Chain, Manufacturing, or a related field Proficiency in SQL Proficiency in Excel including vlookups and pivot tables Experience using data analysis tools such as Power BI or Tableau Experience with data visualization and dashboard development Strong analytical skills and ability to use data to inform decision-making Excellent written and verbal communication skills Proficient in spoken and written English CV must be in English Desirable: Experience with JSON, XML, SOAP, REST technologies Knowledge of data warehousing concepts and data model design Experience with ERP and SaaS platforms (SAP, Oracle, Infor M3, Coupa) Experience in a programming language such as Java, Python, C# or .NET Experience in applied analytics and Machine learning/AI techniques Certifications in data analysis, SQL, or related fields are a plus You’ll love this role if You’re excited about the prospect of working with Supplier Data in the Procurement and Supply Chain domain You’re passionate about analyzing data and drawing insights that will impact business decisions You enjoy solving problems and don’t mind going through multiple iterations until you get the best solution possible You thrive in a continuous learning environment and keep up to date with the latest trends in your field You’re excited about learning from multiple industries and practices as you work through different data domains You may not like this role if… You like working independently as much as possible and don’t like deadlines – this role requires that you collaborate in cross-functional teams to deliver work across one or more projects to satisfy clients and stakeholders You are not interested with interacting with business stakeholders – the ability to understand the business context is key to this role as you will not only need to navigate the data but also know how to prepare the data in such a way that can be used by the business for analysis and insight You expect clear instructions to perform your role – as a data analyst, you may often need to perform your role with limited context and information, and you will need to be open to seeking this out and iterating through multiple solutions You do not like going through the process of cleaning and transforming – data analysts know the reality of how much work needs to be put in to get data to a readily available state and you need to be ready to take on that challenge You do not like debugging SQL queries or find the prospect of seeing large pieces of code scary – to be able to confidently triage, investigate, and resolve issues effectively, debugging is a core part in a data analyst’s workstream. Benefits Work from anywhere within UK - we are a fully remote company. We have a London Office for UK-based employees who wants a change of scenery. Private health insurance. Flexible PTO - We offer 25 days of paid holiday per year England Bank Holidays. Connect and socialize with the team during our company socials and off-site events. We celebrate special occasions with you - like your birthday Additional PTO for all employees during their birthdays. Receive Competitive Pay - Our team makes sure to provide a highly competitive rate based on your skills and location. Work with a diverse, international team. Tons of amazing career opportunities in a fast-growing in-demand industry.

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.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.