Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Senior Data Analyst

DRW
Greater London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst – Fraud Analytics

Senior Data Analyst - SQL & Python

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Job LocationLondonEmployment typeRegularDepartmentTechnologyTargeted Start DateImmediate

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.


We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.


As a Senior Data Analyst you will play an integral role in all operational aspects of onboarding, managing and maintaining various datasets used by traders and quantitative researchers. You will work closely with a variety of stakeholders, including technology, front office, operations, research, and risk management. You should be comfortable investigating complex data support issues and develop sustainable solutions to address root causes


What you will do in this role

Help verify, clean, and ensure data is accurate and consistent across systems used for research and analysis by the various trading teams globally


Analyse datasets in order to draw conclusions and provide insight to address stakeholder or project-related questions
Collect metrics and analyse datasets across different dimensions of data quality including; completeness, validity, accuracy, timeliness, and consistency
Perform preliminary root cause analysis and make recommendations for modifications in data pipelines to increase data quality
Monitor and work through production data issues whilst engaging key stakeholders across multiple teams and facilitating global support
Proactively identify opportunities for improvement in processes and engage with developers to determine the appropriate course of action

What you will need in this role

3+ years of experience working as a data analyst


Knowledge of a variety of financial instruments, in particular exposure to derivatives instruments
Experience working with SQL
Experience with cloud storage solutions
Experience with workflow management tools (Airflow / Argo)
Prior experience writing documentation for senior stakeholders; the ability to accurately abstract and summarize technical information is critical
Python programming skills: PySpark, Pandas, Jupyter Notebooks (3+ years in a professional environment)
Prior experience working with git in a professional environment
Ability to work independently in a fast-paced environment; prioritize multiple tasks and projects

Additional skills or experience which enhance consideration for this role

Prior experience developing data quality control processes to detect data gaps or inaccuracies is a plus


Familiarity with compressed/optimized file formats for data storage such as Parquet and HDF5
Prior experience providing technical guidance to junior data analysts
Prior experience mapping security identifier data or working with a security master database would be beneficial
Prior experience working with Bloomberg Terminal
Familiarity with Linux and basic Bash scripting skills

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Future of Data Science Jobs: Careers That Don’t Exist Yet

Data science has rapidly become one of the most influential disciplines of the digital age. Once a niche combination of statistics and computing, it is now central to how organisations innovate, compete, and grow. From healthcare and finance to retail, logistics, and government, data science is reshaping decision-making across every sector. In the UK, data science has grown into a core career pathway. Salaries are competitive, demand continues to rise, and roles now extend far beyond analytics into artificial intelligence, machine learning, and predictive modelling. Yet as technologies evolve, many of the most important data science careers of the future don’t exist today. This article explores why entirely new roles will emerge, the kinds of careers that may appear, how existing jobs will evolve, why the UK is well placed to lead, and what professionals can do to prepare for this transformation.

Seasonal Hiring Peaks for Data Science Jobs: The Best Months to Apply & Why

The UK's data science sector has matured into one of Europe's most intellectually rewarding and financially attractive technology markets, with roles spanning from junior data analysts to principal data scientists and heads of artificial intelligence. With data science positions commanding salaries from £30,000 for graduate data analysts to £140,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this intellectually stimulating and rapidly evolving field. Unlike traditional analytical roles, data science hiring follows distinct patterns influenced by business intelligence cycles, research funding schedules, and machine learning project timelines. The sector's unique combination of mathematical rigour, business impact requirements, and cutting-edge technology adoption creates predictable hiring windows that strategic professionals can leverage to advance their careers in extracting insights from tomorrow's data. This comprehensive guide explores the optimal timing for data science job applications in the UK, examining how enterprise analytics strategies, academic research cycles, and artificial intelligence initiatives influence recruitment patterns, and why strategic timing can determine whether you join a pioneering AI research team or miss the opportunity to develop the next generation of intelligent systems.

Pre-Employment Checks for Data Science Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in data science reflects the discipline's unique position at the intersection of statistical analysis, machine learning innovation, and strategic business intelligence. Data scientists often have privileged access to comprehensive datasets, proprietary algorithms, and business-critical insights that form the foundation of organisational strategy and competitive positioning. The data science industry operates within complex regulatory frameworks spanning GDPR, sector-specific data protection requirements, and emerging AI governance regulations. Data scientists must demonstrate not only technical competence in statistical modelling and machine learning but also deep understanding of research ethics, data privacy principles, and the societal implications of algorithmic decision-making. Modern data science roles frequently involve analysing personally identifiable information, financial data, healthcare records, and sensitive business intelligence across multiple jurisdictions and regulatory frameworks simultaneously. The combination of analytical privilege, predictive capabilities, and strategic influence makes thorough candidate verification essential for maintaining compliance, security, and public trust in data-driven insights and automated systems.