At a Glance
- Tasks: Partner with teams to transform business needs into data-driven solutions and reports.
- Company: Join a leading investment management firm focused on innovation and collaboration.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic role with global collaboration and exciting career advancement opportunities.
- Why this job: Make an impact by leveraging data analytics in the fast-paced financial services industry.
- Qualifications: Experience in data analytics and proficiency in Python, R, and SQL required.
The predicted salary is between 63000 - 77000 £ per year.
- Partner with Coverage Analysts, Investment Strategy & Research and Multi-Manager Solutions professionals to understand analytical needs
- Translate business needs into data solutions, quantitative models and reporting
- Participate in research discussions and project planning
- Source, validate and maintain investment data across platforms and databases
- Build, maintain and enhance quantitative models, analytical tools and performance attribution systems
- Support backtesting, scenario analysis and factor-based research
- Automate analytical and reporting workflows for performance reports, risk metrics and strategy dashboards
- Design and maintain dashboards and data visualisations
- Apply model governance practices, including documentation, version control and validation protocols
- Evaluate new technologies and methodologies, including artificial intelligence and machine learning
- Support product development and market research through data analysis and quantitative modelling
- Collaborate with Enterprise Technology, Information Technology and Investment Risk Management teams on technology enhancements and platform development
- Coordinate with colleagues across Boston, New York, London and India
Requirements
- Prior experience in data analytics, quantitative development or reporting within investment management or financial services
- Strong knowledge of investment data, portfolio analytics, performance attribution and risk
- Bachelor's or Master's degree in mathematics, statistics, computer science, data science or a related quantitative field
- Advanced proficiency in Python, R and Structured Query Language (SQL)
- Experience using database platforms
- Strong communication skills and ability to explain complex concepts to technical and non-technical audiences
- Ability to collaborate across functions and locations
- Ability to manage multiple priorities and deliver high-quality work to deadlines
- Initiative, intellectual curiosity and practical problem-solving mindset
- Professional certification such as Chartered Financial Analyst (CFA) or Financial Risk Manager (FRM) is preferred
- Experience with cloud platforms such as Amazon Web Services or Microsoft Azure, big data technologies or business intelligence tools is preferred
- Experience with investment data platforms such as Bloomberg, Fact Set, Morningstar, e Vestment or Aladdin is preferred
- Background in investment consulting, multi-manager investing or investment operations is preferred
- Core Competencies
Demonstrates expertise in data analytics and quantitative modeling within investment management, utilizing advanced programming skills in Python, R, and SQL to develop data solutions and performance attribution systems.
Strong ability to collaborate across teams and communicate complex concepts effectively.
- Highest-signal resume keywords
- Data Analytics
- Quantitative Modeling
- Performance Attribution
- Python Programming
- Investment Data Management
- ATS Optimization Keywords
- Hard Skills
- Data Analytics
- Quantitative Development
- Performance Attribution
- Python
- R
- SQL
- Data Visualization
- Model Governance
- Backtesting
- Scenario Analysis
- Soft Skills
- Strong Communication
- Collaboration
- Problem-Solving
- Intellectual Curiosity
- Initiative
Certifications & Qualifications
- Chartered Financial Analyst
- Financial Risk Manager
- Industry Keywords
- Investment Management
- Financial Services
- Portfolio Analytics
- Risk Management
- Investment Consulting
- Multi-Manager Investing
- Investment Operations
- Tools & Technologies
- Amazon Web Services
- Microsoft Azure
- Bloomberg
- Fact Set
- Morningstar
- EVestment
- Aladdin
- Business Intelligence Tools
- Big Data Technologies
- Database Platforms
- #J-18808-Ljbffr
Data Analytics & Reporting Analyst – Data Engineering Team in London employer: Jobtailor
As a Client Services Coordinator at our dynamic company, you will thrive in a supportive work culture that prioritises employee growth and development. We offer comprehensive training, opportunities for advancement, and a collaborative environment where your contributions are valued. Located in a vibrant area, our team enjoys a healthy work-life balance and the chance to engage with diverse clients, making every day rewarding and meaningful.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analytics & Reporting Analyst – Data Engineering Team in 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 Jobtailor!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Analytics & Reporting Analyst – Data Engineering Team at Jobtailor.
✨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 Jobtailor.
✨Apply Directly through Our Website
When you find a suitable opening like Data Analytics & Reporting Analyst – Data Engineering Team at Jobtailor, 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 Data Analytics & Reporting Analyst – Data Engineering Team in 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 Jobtailor, 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 Jobtailor. 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 Jobtailor
✨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 Jobtailor!
✨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.
