At a Glance
- Tasks: Transform data into actionable insights to enhance customer understanding and business performance.
- Company: Join a global leader in market transparency and strategic decision-making.
- Benefits: Generous holiday allowance, health benefits, and a competitive pension scheme.
- Other info: Collaborative environment with opportunities for continuous learning and career growth.
- Why this job: Dive into data science and AI while making a real impact on customer engagement.
- Qualifications: Proficiency in SQL, Python, and data visualisation tools like Power BI.
The predicted salary is between 35000 - 42000 £ per year.
We help companies make strategic, sustainable decisions by bringing transparency to markets across the world. We create a comprehensive view of commodities markets, providing companies with the data and intelligence to successfully navigate across global value chains every day. Our customers benefit from instant access to price assessments, reports and forecasts, a dedicated news channel and supply and demand data.
To provide dedicated analytical capability within Customer Intelligence, connecting customer research, CRM data, product usage data and business performance metrics into clear, actionable insight. This role is designed to build future data science and AI capability while strengthening day-to-day reporting, dashboarding and evidence-based decision making.
You will be responsible for turning customer, commercial and operational data into practical insight that improves customer understanding, product decisions, retention, engagement and business performance. You will work closely with customer researchers and cross-functional partners to bring together quantitative and qualitative evidence, helping the business move towards a more connected view of customer needs, behaviours and outcomes. You will have exposure to data science, automation, AI-ready analytics, cloud environments and customer data architecture.
- Analytics and Insight Generation: Analyse customer, product, commercial and operational data to uncover trends, risks and opportunities, delivering insights into customer behaviour, engagement, retention, product adoption and experience. Conduct ad hoc analysis to support strategic initiatives and leadership decisions, while collaborating with Customer Insights teams to combine quantitative data and customer research into actionable recommendations.
- Data Management and Reporting: Extract, clean and analyse data using SQL, Python and Excel to support reporting, dashboards and insight packs. Track key customer and business metrics such as NPS, engagement, retention, adoption and usage, while ensuring data is validated, consistent and reliable for decision-making.
- Data Science, Automation and AI Readiness: Use Python to automate recurring analysis, reporting and data preparation, while supporting statistical modelling, predictive analytics and AI/data science proof-of-concept work.
- Data Visualisation and Storytelling: Create impactful Power BI dashboards and visualisations to communicate customer and business performance, translating complex analysis into clear, actionable insights for technical and non-technical audiences. Support the development of leadership-ready reports, presentations and data-driven recommendations that explain what is happening, why it matters and what actions should follow.
Promote knowledge sharing and a unified view of customer data, while supporting a culture of evidence-based decision-making through the effective use of data and insights.
- Excellent data science and programming skills, with proficiency in Python for data analysis, modelling, automation and statistical applications.
- Experience in data manipulation, querying and analysis using SQL.
- Skilled in data visualisation and presentation of analytical findings using Power BI.
- Competent in Microsoft Excel for data analysis, reporting and business insight generation.
- Exceptional attention to detail, especially around data quality, accuracy and interpretation.
- Experience using Salesforce and understanding of how CRM data can support analytics and decision-making.
- Understanding of data architecture concepts, including data warehousing and data lakes.
- Exposure to cloud computing environments such as Microsoft Azure.
- Exposure to predictive analytics, machine learning, AI-enabled analytics or advanced statistical methods.
- Experience working with customer, commercial, subscription, product usage or behavioural datasets.
- Demonstrates curiosity by asking thoughtful questions, challenging assumptions and looking for better ways to use data to understand customers and business performance.
- Shows a willingness to learn new tools, techniques and technologies, including Python, SQL, Power BI, automation, data science and AI-enabled analytics.
- Uses evidence objectively, explaining what the data does and does not show, and avoids jumping to conclusions without enough context.
- Maintains high standards of data quality, accuracy and interpretation so that insight and recommendations are reliable.
- Works collaboratively across Customer Insights, Product, Commercial, Technology and Data teams to build a more joined-up view of the customer.
- Shares learning openly, seeks input from others and helps translate business questions into clear analytical approaches.
- Connects analysis to customer value and business outcomes, making sure insight supports better decisions and practical action.
Generous holiday allowance with the option to buy additional days, health screening, eye care vouchers and private medical benefits, wellbeing programs, life assurance, access to a competitive contributory pension scheme, save as you earn share option scheme, travel season ticket loan, electric vehicle scheme, optional dental insurance, maternity, paternity and shared parental leave, employee assistance programme, access to emergency care for both the elderly and children, access to employee discounts scheme via Perks at Work.
Insight Analyst (Commercial) SQL in City of London employer: ICIS
ICIS is an exceptional employer that prioritises employee wellbeing and professional growth, offering a generous holiday allowance, comprehensive health benefits, and extensive learning resources. Our collaborative work culture fosters innovation and accountability, ensuring that every team member's contributions are valued and impactful. Located in a dynamic industry, this role provides the opportunity to shape meaningful marketing strategies that drive commercial success while making a positive difference in global resource optimisation.
StudySmarter Expert Advice🤫
We think this is how you could land Insight Analyst (Commercial) SQL in City of London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like ICIS!
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✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like ICIS.
✨Apply Directly through Our Website
When you find a suitable opening like Insight Analyst (Commercial) SQL at ICIS, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Insight Analyst (Commercial) SQL in City of London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at ICIS, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at ICIS. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at ICIS
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at ICIS!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
