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For Companies At a Glance
- Tasks: Join our team to analyse data and create impactful visualisations for investment management.
- Company: Be part of a leading global investment management firm shaping the future of finance.
- Benefits: Enjoy a competitive salary, bonuses, and flexible working with 4 days in the office.
- Why this job: Make a real impact with your data skills while collaborating in a dynamic, innovative environment.
- Qualifications: Proficiency in SQL, Tableau, Power BI, and a strong understanding of asset management is essential.
- Other info: This role offers opportunities for professional growth and development in a fast-paced industry.
The predicted salary is between 72000 - 108000 £ per year.
Our client is one of global investment management companies. They are looking for Senior Data & Analytics Analyst to join the teams in London. Permanent, 4 days in office
Salary is up to £90k base + bonus + benefits
Primary Responsibilities:
Business Insight & Visualization
- Partner with business units to understand investment management data needs and deliver impactful analytics solutions.
- Collect, analyze, and interpret large datasets using SQL and advanced data analysis techniques.
- Design and develop dashboards and reports in Tableau and Power BI to communicate insights clearly to stakeholders.
- Create data-driven recommendations to enhance portfolio management, risk assessment, and operational efficiency.
Technical Agility
- Independently analyze business processes, identify improvement opportunities, and propose data-driven solutions.
- Establish and promote best practices in SQL development, dashboard design, and analytics workflows.
- Ensure data integrity, accuracy, and compliance with industry standards in investment management.
Data Strategy & Literacy
- Lead initiatives to improve data literacy across teams, including training on analytics tools and visualization best practices.
- Manage analytics roadmaps and prioritize projects that deliver high business impact.
Skills & Qualifications:
- Technical Skills: Tableau, Power BI, SQL, advanced Excel, data modeling, data transformation, statistical analysis.
- Domain Expertise: deep understanding of the asset management industry, investment operations business model, and investment process, data, and systems flow.
- Able to help shape a vision for transforming existing capabilities leveraging understanding of industry trends, understanding of the IO business and technology tools to advance organizational goals.
- Proficient in using various data, technologies and analytical tools. Stays updated with the emerging technological trends and best practices to drive business transformation
- Strong problem-solving, strategic thinking, and data storytelling abilities.
- Excellent interpersonal skills to influence and engage stakeholders at all levels.
- Proven ability to work in agile, fast-paced environments.
Senior Data Analytics Analyst employer: McCabe & Barton
Contact Detail:
McCabe & Barton Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Analytics Analyst
✨Tip Number 1
Familiarise yourself with the latest trends in data analytics and investment management. Understanding the current landscape will help you speak confidently about how your skills can contribute to the company's goals during interviews.
✨Tip Number 2
Network with professionals in the investment management sector, especially those who work with data analytics. Attend industry events or webinars to make connections that could lead to referrals or insider information about the role.
✨Tip Number 3
Prepare to discuss specific projects where you've successfully used SQL, Tableau, or Power BI to drive business insights. Having concrete examples ready will demonstrate your technical agility and problem-solving skills.
✨Tip Number 4
Showcase your ability to communicate complex data insights clearly. Practice explaining your past analytics projects to someone without a technical background, as this will highlight your data storytelling abilities, which are crucial for engaging stakeholders.
We think you need these skills to ace Senior Data Analytics Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data analytics, SQL, and tools like Tableau and Power BI. Use specific examples that demonstrate your ability to deliver impactful analytics solutions.
Craft a Compelling Cover Letter: In your cover letter, express your understanding of the asset management industry and how your skills align with the company's needs. Mention your experience in improving data literacy and driving business transformation.
Showcase Technical Skills: Clearly outline your technical skills in SQL, data modelling, and statistical analysis. Provide examples of how you've used these skills to create data-driven recommendations or improve business processes.
Highlight Interpersonal Skills: Since the role requires excellent interpersonal skills, include examples of how you've influenced stakeholders or led training initiatives. This will demonstrate your ability to engage effectively with teams and drive collaboration.
How to prepare for a job interview at McCabe & Barton
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, Tableau, and Power BI in detail. Bring examples of dashboards or reports you've created, and be ready to explain the thought process behind your data analysis techniques.
✨Understand the Investment Management Industry
Familiarise yourself with the asset management industry and its operations. Being able to speak knowledgeably about industry trends and how they impact data analytics will demonstrate your expertise and commitment to the role.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities and strategic thinking. Prepare to discuss specific situations where you identified improvement opportunities and implemented data-driven solutions.
✨Emphasise Communication Skills
Since the role involves engaging with stakeholders, highlight your interpersonal skills. Be ready to discuss how you've effectively communicated complex data insights to non-technical audiences in the past.
