Job Title: Data Analyst

Location: London (SOHO – 2 Days a week onsite)

Salary: £35,000 - £40,000

Overview:

The Client is a Software specialist growth equity firm with offices in London and Boston. Who partners with rapidly growing software start-ups that are thriving off lower external funding. The firm brings capital for growth initiatives and shareholder liquidity and highly relevant operational expertise.

Job Summary:

They are seeking a skilled and analytical Data Analyst to join the team. The ideal candidate will have a strong understanding of data analytics, and statistical methods, and the ability to interpret complex data sets. Along with a strong STEM background / Degree from a Redbrick University! This role will involve analysing trends, creating insightful reports, and providing recommendations to drive data-driven decisions and optimise business performance.

Key Responsibilities:

• Data Collection & Analysis: Gather, process, and analyse large sets of data from various sources, ensuring data accuracy and integrity.
• Data Quality Assurance: Identify, troubleshoot, and resolve data discrepancies and quality issues.
• Reporting & Insights: Present findings to stakeholders through reports and presentations, translating data insights into business actions.
• Collaboration: Work with cross-functional teams (finance, operations) to understand data needs, and provide analytical support to drive key projects and initiatives.
• Predictive Analysis: Utilise statistical techniques and predictive models to forecast future trends and outcomes.
• Documentation: Maintain and update documentation for processes, analyses, and data sources.

Requirements:

• Education: Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. (ideally from Redbrick University)
• Experience: Could be open to Graduate up to 4 years of experience as Data Analyst
• Technical Skills:
• Proficiency in SQL for data extraction and manipulation.
• Strong skills in Excel, and experience with statistical tools like R or Python is a plus.
• Familiarity with data warehousing and ETL processes.
• Analytical Skills: Ability to analyse complex data sets, identify patterns, and draw actionable insights.
• Communication: Excellent verbal and written communication skills, with the ability to convey complex data findings in a clear and actionable manner.
• Problem-Solving: Strong problem-solving abilities with a detail-oriented and data-driven mindset.

Preferred Qualifications:

• Experience in (industry, e.g., Software, FinTech, Finance, SaaS or relevant).
• MSc in STEM subject.
• Knowledge of machine learning and predictive modeling.
• Advanced experience with Python or R for data manipulation and statistical analysis.