Financial Data Analyst - Securities Russian speaker

Project Recruit
London
7 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst - Finance and Treasury

Data Analyst

Data Analyst - Hedge Fund

Data Analyst

ERP Analyst

Data Engineer (Financial Data Platform)

Financial Data Analyst - Securities (Russian speaker)

Our client, a leading organization in finance and technology, is seeking motivated and detail-oriented Russian speakers to join their dynamic Securities team. This is a 6-month temporary contract with an immediate start date and would suit a candidate with a strong analytical mind and demonstratable interest in financial markets.

This is a great opportunity for graduates to begin their career within a leading organisation in the technology and finance industry. Successful applicants will receive world-class training, work in a complex and exciting environment, and have the opportunity to apply for permanent roles within the company.

The successful candidates will be responsible for performing entity research, updating databases, and performing data quality checks, while also supporting ad hoc projects to enhance data quality, timeliness, and coverage.

Ideal candidate should be a Native/Fluent Russian speaker and have a solid background in financial data. They should also have a strong interest in developing technical skills.

Key Responsibilities:

  • Conduct entity research and database updates, including but not limited to, name identification (alternative names, former names, name in local language), business card data (company website, domicile address, registered address), identifiers (registry ID, legal entity identifier) and hierarchy research (bottom-up ultimate parent review, top-down subsidiary list review).
  • Acquire and research the source documentation for explicitly sanctioned entities for the Client's covered jurisdictions and capture relevant sanctions data which will be defined in the training manuals provided by the Client.
  • Performing data quality checks and other ad hoc projects to improve data quality and timeliness or expand data coverage.

Key Requirements:

  • Native or fluent Russian speaker with strong written and verbal communication skills.
  • Previous experience with Data Quality Checks.
  • Background in financial data or a related field.
  • Strong research and analytical skills with high attention to detail.
  • Proficiency in Microsoft Excel and an interest in developing technical skills.
  • Proficiency in programming languages would be a plus.
  • Proactive approach to problem-solving and a commitment to delivering high-quality results.
  • Ability to work effectively in a remote setting and handle sensitive information with professionalism.

Unfortunately, we are only able to contact applicants who are successful to interview stage.

We are an equal opportunities employer and welcome applicants from all sections of the community, regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation, and transgender status.

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!