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- Tasks: Use data science to drive insights and enhance business intelligence.
- Company: Join Parmenion, a leading UK investment platform focused on data-driven decisions.
- Benefits: Permanent role with competitive salary and opportunities for professional growth.
- Other info: Collaborative team culture with a focus on continuous improvement and innovation.
- Why this job: Kickstart your data science career with hands-on experience in a modern analytics environment.
- Qualifications: Degree in a quantitative field or equivalent experience; strong SQL and Python skills required.
The predicted salary is between 30000 - 40000 £ per year.
Department: Admin and Management
Reports To: Business Intelligence Manager
Location: Bristol
Contract Type: Permanent, Full-Time
About Us
Parmenion is a UK-based investment platform helping clients manage and grow their wealth. Our Business Intelligence team sits at the heart of data-driven decision-making, delivering insights that shape product strategy, commercial performance, and customer experience.
Role Overview
This role supports the continued evolution of Parmenion’s data-driven decision-making by going beyond foundational reporting to incorporate predictive analytics, statistical modelling, and advanced data visualisation. As a Junior Data Scientist within the BI team, you will leverage data science techniques to enhance the quality, depth, and impact of our business intelligence output. Working closely with the Delivery, Finance, and Technology teams, you will help ensure that reporting solutions and analytical insights remain accurate, scalable, and impactful. This is an excellent opportunity for someone early in their data science career who wants hands-on exposure to a modern analytics stack built on Microsoft Fabric and Power BI, while contributing meaningfully to business outcomes.
Key Responsibilities
- Write and optimise SQL queries to extract, transform, and analyse data from our data lakehouse and warehouse environments within Microsoft Fabric.
- Build and maintain interactive dashboards and reports in Power BI, ensuring data accuracy and a strong user experience for stakeholders.
- Develop and support Python-based data pipelines, automation scripts, and exploratory analyses.
- Collaborate with the wider BI and data engineering team to improve data models, quality, and governance.
- Conduct ad-hoc analysis to support commercial, product, and operational teams with evidence-based recommendations.
- Assist with the design and implementation of statistical models, segmentation, and forecasting where appropriate.
- Contribute to documentation, knowledge-sharing, and continuous improvement within the BI function.
- Stay current with developments in data science tooling, Microsoft Fabric, and best practices in business intelligence.
Essential Skills & Experience
- Strong SQL skills with experience writing complex queries for data extraction, transformation, and analysis.
- Working knowledge of Python for automation.
- Experience building dashboards and reports in Power BI, including DAX measures and data modelling.
- Familiarity with Microsoft Fabric or similar cloud-based data platforms (e.g., Azure Synapse, Databricks).
- A solid understanding of statistics and data analysis fundamentals.
- Good communication skills with the ability to present findings clearly to non-technical audiences.
- A proactive, self-starting approach with strong attention to detail.
Desirable Skills & Experience
- Experience working in financial services, fintech, or investment platforms.
- Knowledge of data engineering concepts such as ETL/ELT pipelines.
- Exposure to version control (Git) and collaborative development workflows.
- Familiarity with machine learning techniques and their practical application in a business context.
- Experience with Fabric-specific components such as notebooks, lakehouses, or data pipelines.
Qualifications
A degree in a quantitative discipline (e.g., Data Science, Computer Science, Mathematics, Statistics, Economics, Engineering) or equivalent practical experience. Relevant professional certifications (e.g., Microsoft PL-300, DP-600) are a plus but not required.
Parmenion is a solo enhanced firm regulated under the Financial Conduct Authority. This is not a certified role under SMCR. The FCA have conduct rules that firms and individuals must follow to ensure that they act with integrity and treat customers fairly. You will champion these rules:
- The conduct rules: You must act with integrity
- You must act with due skill, care and diligence
- You must be open and cooperative with the FCA, the PRA and other regulators.
- You must pay due regard to the interests of customers and treat them fairly.
- You must observe proper standards of market conduct
- You must act to deliver good outcomes for retail customers
And will inspire by living our values:
- Getting the job done
- You being you
- Making tomorrow better than today
Junior Data Scientist in Bristol employer: Parmenion
Contact Detail:
Parmenion Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior Data Scientist in Bristol
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, dashboards, and any predictive models you've built. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. Get comfortable explaining your thought process and how you approach problem-solving. Remember, it's all about demonstrating your analytical mindset!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at Parmenion. Don’t miss out!
We think you need these skills to ace Junior Data Scientist in Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Junior Data Scientist role. Highlight your SQL skills, Python experience, and any relevant projects or coursework that showcase your data science abilities. We want to see how you can contribute to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your skills align with our mission at Parmenion. Keep it concise but impactful – we love a good story!
Showcase Your Projects: If you've worked on any data-related projects, whether in school or on your own, make sure to mention them. Include links to dashboards or reports you've created, especially if they involve Power BI or Python. We’re keen to see your hands-on experience!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Parmenion
✨Know Your SQL Inside Out
Since strong SQL skills are essential for this role, make sure you brush up on writing complex queries. Prepare examples of how you've used SQL in past projects or studies, and be ready to discuss your thought process when extracting and transforming data.
✨Show Off Your Python Skills
Familiarity with Python is a must, so come prepared with examples of automation scripts or data pipelines you've developed. If you can, demonstrate your understanding of how Python can enhance data analysis and reporting during the interview.
✨Dashboards That Dazzle
As you'll be building interactive dashboards in Power BI, think about your previous experiences with visualisation tools. Bring along a portfolio or screenshots of dashboards you've created, and be ready to explain your design choices and how they improved user experience.
✨Communicate Clearly
Good communication skills are key, especially when presenting findings to non-technical audiences. Practice explaining complex data concepts in simple terms, and prepare to discuss how you've successfully communicated insights in the past.