Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead data analytics projects, delivering insights through statistical analysis and collaboration.
- Company: Join JPMorgan Chase's innovative Global Technology team.
- Benefits: Competitive salary, career growth, and opportunities to work with cutting-edge technology.
- Why this job: Make a real impact by shaping technology strategies and driving data-driven decisions.
- Qualifications: Degree in relevant field and 5+ years of experience in data analytics.
- Other info: Dynamic environment with mentorship opportunities and a focus on continuous learning.
The predicted salary is between 48000 - 72000 £ per year.
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Data Analytics Engineer at JPMorgan Chase within the Global Technology - Analytics, Insights and Measurements (GT AIM) team, you will deliver trusted, decision-grade insight across GT through rigorous statistical analysis and domain-informed interpretation. You will be entrusted in delivering market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Reporting to the Head of GT Architecture and Strategy (GTAS), this role applies sound statistical and analytical methods to technology data to inform strategy, execution, and investment decisions across multiple technology domains. The role works in close partnership with leaders of strategic programs, providing continuous statistical analysis and insight to support priority outcomes.
The role requires deep understanding of software engineering delivery models and flows e.g., feature branch, trunk-based, and integrated delivery to ensure metrics and analysis accurately reflect how technology is delivered. Areas of focus include developer productivity, delivery and portfolio performance, technology spend and value realization, return on investment, and the adoption and impact of Artificial Intelligence across GT.
The emphasis is on building internally owned, transparent, and explainable analytics through sound statistical methods, rather than relying on opaque third-party tools. All roles are hands-on. Managers provide leadership and direction while actively contributing to analysis and insight delivery. Senior Individual Contributors independently own complex analytical problems and influence outcomes through expertise and insight.
Job responsibilities:
- Define, create, deliver, establish and maintain a metrics framework and complementary visuals aligned to CTO and technology leadership decision needs.
- Build strong relationships across various GT functions.
- Communicate statistical findings effectively to technical and non-technical audiences without oversimplification or false precision.
- Work closely to JPMC key strategic programs and initiatives, while providing continuous analysis & insights to support their priority outcomes, all with sound statistical measures.
Statistical Analysis and Data Interpretation:
- Continuously refine analytical approaches as technology strategy, architecture, and delivery practices evolve.
- Support technology leadership in understanding trade-offs, risks, opportunities, and uncertainty.
- Collaborate closely with engineering, platform, architecture, and AI enablement teams to understand delivery practices, workflows and constraints.
- Perform hands-on statistical analysis using appropriate descriptive, inferential, and exploratory techniques.
- Evaluate distributions, trends, and changes over time while accounting for structural differences in teams, systems, and delivery models.
Operations, Measurements and Instrumentation:
- Identify required data points needed to answer key analytical and statistical questions, then define requirements for instrumenting data at the source.
- Ensure metrics are compatible with different engineering flows, including feature branch development, trunk-based development, and integrated delivery.
- Improve data quality, consistency, and traceability over time.
- Ensure reporting supports informed decision-making rather than metric consumption without context.
Required qualifications, capabilities, and skills:
- Degree in Mathematics, Statistics, Data Science, Engineering, Computer Science or equivalent 5+ years applicable work experience.
- 7+ years experience performing statistical analytics, data science, or performance measurement roles.
- Practical experience working with technology, delivery, portfolio, financial, or AI-related data.
- Demonstrated experience applying statistical methods to real-world, imperfect datasets and evolving delivery practices.
- Strong familiarity with concepts such as statistical significance, confidence intervals, variability, and margin of error.
- Proficiencies in a modern data stack: Excel, Python, R Studio, Power BI, Tableau, Qlik, SQL, dbt, Databricks, Snowflake, and Microsoft Fabric.
Preferred qualifications, capabilities, and skills:
- Desire and ability to mentor peers through statistical expertise and engineering domain knowledge.
- Strong formal training in statistics.
- Intellectual curiosity and commitment to statistical rigor.
- Respect for the complexity and variability of software delivery systems within a large enterprise.
- Practical cloud native experience.
- Proficient in all aspects of the Software Development Life Cycle.
- Proficiency in automation and continuous delivery methods (CI/CD pipelines).
Lead Data Analytics Engineer - Global Technology Analytics, Insights and Metrics in London employer: J.P. Morgan
Contact Detail:
J.P. Morgan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Analytics Engineer - Global Technology Analytics, Insights and Metrics in London
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works at JPMorganChase. Building relationships can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio of projects or analyses, make sure to highlight them. Create a personal website or use platforms like GitHub to showcase your work. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by diving deep into the role. Understand the key metrics and technologies mentioned in the job description. Be ready to discuss how your experience aligns with their needs, especially around statistical analysis and technology delivery.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the StudySmarter family. Let’s get you that dream job!
We think you need these skills to ace Lead Data Analytics Engineer - Global Technology Analytics, Insights and Metrics in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Data Analytics Engineer role. Highlight your experience with statistical analysis and data interpretation, and don’t forget to mention any relevant technologies you’ve worked with. We want to see how your skills align with what we’re looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about this role and how your background makes you a perfect fit. Be sure to mention your understanding of software engineering delivery models and how you can contribute to our team.
Showcase Your Analytical Skills: In your application, provide examples of how you've applied statistical methods to real-world problems. We love seeing concrete examples that demonstrate your analytical prowess and how you’ve influenced outcomes in previous roles.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at J.P. Morgan
✨Know Your Stats
Brush up on your statistical methods and be ready to discuss how you've applied them in real-world scenarios. Be prepared to explain concepts like confidence intervals and statistical significance, as these will likely come up during the interview.
✨Showcase Your Technical Skills
Make sure you can demonstrate your proficiency with tools like Python, SQL, and Power BI. Bring examples of past projects where you've used these technologies to deliver insights or solve complex problems, as this will show your hands-on experience.
✨Communicate Clearly
Practice explaining complex analytical findings in simple terms. You’ll need to convey your insights to both technical and non-technical audiences, so being able to articulate your thoughts clearly is crucial.
✨Understand the Business Context
Familiarise yourself with JPMorgan Chase's business objectives and how your role as a Lead Data Analytics Engineer fits into their strategy. This will help you align your answers with their goals and demonstrate your understanding of the bigger picture.
