At a Glance
- Tasks: Bridge data engineers and business needs, delivering insightful reports and analytics.
- Company: Join MiQ, a diverse and inclusive tech company that values passion and determination.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and continuous improvement.
- Why this job: Make an impact by transforming data into actionable insights and driving business success.
- Qualifications: Experience with data visualisation tools, SQL, and a problem-solving mindset.
The predicted salary is between 30000 - 40000 £ per year.
We love different personalities at MiQ and strive to build teams constructed with diverse backgrounds and inclusive points of view. That said, we firmly believe that our values make us stronger and we look for people who share our values below.
- Passion - We love and live what we do.
- Determination - We always find a way to 'figure it out'.
- Unity - We hold each other accountable. We win and lose as a team.
- Agility - We anticipate the unexpected, embrace and adapt to change.
- Courage - We dare to think unconventionally.
You will be the bridge between the data engineers and the rest of the business, facilitating the reporting needs, communicating those needs back to the data team and delivering the reporting requested. You will work on a range of revenue-focused projects including automation and streamlining of forecasting processes, pipeline analysis, revenue intelligence, goal setting and tracking, insights and reporting.
Key areas of focus:
- Commercial Dashboarding, Reporting and insights
- Pipeline and Sales Cycle Reporting and Analysis
- Data-driven forecasting of revenue and gross profit (through statistical models)
- Data quality, accuracy & systems alignment
- Support Commercial BI Manager & broader Rev Ops team on key projects
- Ad Hoc commercial data / analytics / insights requests
Responsibilities:
- Create repeatable revenue and profit analysis, insight and recommendations.
- Creation of Dashboards, visualizations and custom reports
- Enrich commercial intelligence via the addition of data sets/metrics e.g. commercial deals, retention and churn, quotas, activity tracking
- Automate the quarterly & monthly forecasting process.
- Own, maintain and report on Seller Quotas, Pipeline forecast reports, win rates, retention, Regional Forecasting, Commercial deals.
- Create technical documentation
- Deliver ad hoc reporting / insight / analysis for Commercial Departments / Leadership
- Accomplishing tasks on time and to a high quality, managing different deadlines and priorities.
Project Management:
- Drive on time completion of key projects and manage stakeholders and management.
- Identify business requirements and work with stakeholders throughout the project.
- Drive adoption of new dashboards, processes, or systems.
- Staying focused and contributing to projects. Organizing stakeholders and multiple milestones.
Internal Collaboration:
- Navigate established relationships with key stakeholders to ensure alignment and updating on key projects.
- Work closely with Revenue Operations, Commercial teams (Sales, Client Success, Trading), Product, Marketing and Finance.
- Work with Global BI and FP&A teams to ensure data quality of projects / workstreams
- Working with internal stakeholders, building relationships and working across differences to find solutions.
Communication:
- Communicate proactively with stakeholders throughout the project to gather inputs, keep them updated, and coordinate.
- Deliver training to key users across multiple departments
- Regularly seek feedback from stakeholders to drive continuous improvement.
- Communicate and present insights and analytics that are actionable and scalable
- Strong ability to document any/all established work
- Great communicator to external partners/clients or internal stakeholders and an understanding of different audiences and requirements.
Innovation:
- Use world-class visualisation tools to deliver analytics that aid forecasting and predictive modelling.
- Always look to automate existing processes and workflows.
- Explore new strategies for transforming manual processes into digital solutions (e.g. AI utilization)
Requirements:
- This role requires strong experience with data visualization tools, advanced Excel, data management, data flows and SQL coding.
- A problem solver with a growth mindset is required and a working knowledge of Enterprise level CRM, ERP, Data visualization and AI tools is preferred.
- Advanced data visualisation experience in a BI tool (Experience in developing Dashboards, Excel models, PowerPoint, Slack and other real-time notifications).
- Proficiency in SQL
- Experience with enterprise level CRM and/or ERP platforms (e.g. Salesforce)
- Knowledge of data governance, including data quality, security, and compliance.
- Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and cloud-based data storage (e.g., S3, Google Cloud Storage)
Nice to Have:
- Experience with programming languages such as Python or R
- Experience working with AI platforms
- Experience with data modelling and data architecture design
- An understanding of machine learning algorithms for regression, classification, clustering, and time series forecasting
Jr Data Analyst - BI in City of Westminster employer: MiQ Digital
At MiQ, we pride ourselves on fostering a vibrant and inclusive work culture that celebrates diverse perspectives and encourages personal growth. As a Jr Data Analyst in our dynamic team, you'll have the opportunity to engage in meaningful projects that drive revenue intelligence while benefiting from comprehensive training and development programmes. Our commitment to innovation and collaboration ensures that you will thrive in an environment where your contributions are valued and your career can flourish.
StudySmarter Expert Advice🤫
We think this is how you could land Jr Data Analyst - BI in City of Westminster
✨Embrace Online Competitions
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We think you need these skills to ace Jr Data Analyst - BI in City of Westminster
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at MiQ Digital, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at MiQ Digital aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
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How to prepare for a job interview at MiQ Digital
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
