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

View Open Roles

Data Scientist

DTCC
London
3 weeks ago
Create job alert

Are you ready to make an impact at DTCC?


Do you want to work on innovative projects, collaborate with a dynamic and supportive team, and receive investment in your professional development? At DTCC, we are at the forefront of innovation in the financial markets. We are committed to helping our employees grow and succeed. We believe that you have the skills and drive to make a real impact. We foster a thriving internal community and are committed to creating a workplace that looks like the world that we serve.

The Information Technology group delivers secure, reliable technology solutions that enable DTCC to be the trusted infrastructure of the global capital markets. The team delivers high-quality information through activities that include development of essential, building infrastructure capabilities to meet client needs and implementing data standards and governance.

Pay and Benefits:

Competitive compensation, including base pay and annual incentive Comprehensive health and life insurance and well-being benefits Pension / Retirement benefits Paid Time Off and Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and well-being. DTCC offers a flexible/hybrid model of 3 days onsite and 2 days remote (Tuesdays, Wednesdays and a day unique to each team or employee).

The impact you will have in this role:

We're seeking a passionate, hands-on and AI/ML Engineer to join our dynamic Technology and Research team, where you’ll play a pivotal role in spearheading AI initiatives and innovation. As an AI/ML Engineer, you will design, develop, and deploy Artificial Intelligence systems that solve complex problems and drive our technological advancement.

What You'll Do

Your Primary Responsibilities:



Generative AI Application Development

Develop and implement AI solutions such as Retrieval-Augmented Generation (RAG) and Agentic Workflows using advanced techniques in prompt engineering and fine-tuning of Large Language Models (LLMs). Conduct thorough evaluations of LLMs to ensure the models meet the desired performance criteria and are aligned with business goals. Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows, enhancing overall efficiency and capabilities.

Model Development and Deployment

Design and develop machine learning models and algorithms to address business challenges and improve product features. Deploy machine learning models in production environments to ensure scalability and efficiency. Optimize and refine models based on performance metrics and feedback.

Data Management

Collect, clean, and preprocess data from various sources to create robust datasets for training and evaluation. Implement data augmentation and feature engineering techniques to enhance model performance. Maintain and manage data pipelines to ensure seamless data flow and integration.

Research and Innovation

Stay updated with the latest trends and advancements in AI and machine learning technologies. Conduct research to explore new methodologies and techniques that can be applied to current and future projects. Collaborate with cross-functional teams to drive innovation and implement cutting-edge solutions.

Collaboration and Communication

Work closely with software engineers, data scientists, and product managers to align AI/ML initiatives with business goals. Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner. Provide mentorship and guidance to junior team members and contribute to the upskilling of the team.

**NOTE: The Primary Responsibilities of this role are not limited to the details above. **



Sound Like You?

6+ years Business Analysis/Solution Design/Software Development experience preferred Bachelor’s degree preferred or equivalent experience, with concentration in Computer Science, Business Administration or related concentration preferred

Additional Qualifications

Strong understanding of statistical methods, data structures, and algorithms. Strong programming skills in Python; experience with Machine Learning libraries and Generative AI frameworks (e.g., Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, PyTorch, scikit-learn, LangChain) and LLMs. Experience developing and deploying AI solutions on AWS cloud platform. Additionally, experience on Snowflake Cortex is plus. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for deploying AI solutions. Proven experience in developing and deploying machine learning models in a production environment. Experience working with large datasets and performing data analysis. Previous experience in a similar role or industry is preferred. Excellent communication and collaboration skills. Strong problem-solving skills and analytical thinking Passion for learning and staying up-to-date with the latest

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist - Hybrid

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.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

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

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.

Why Now Is the Perfect Time to Launch Your Career in Machine Learning: The UK's Intelligence Revolution

The United Kingdom stands at the epicentre of a machine learning revolution that's fundamentally transforming how we solve problems, deliver services, and unlock insights from data at unprecedented scale. From the AI-powered diagnostic systems revolutionising healthcare in Manchester to the algorithmic trading platforms driving London's financial markets, Britain's embrace of intelligent systems has created an extraordinary demand for skilled machine learning professionals that dramatically exceeds the current talent supply. If you've been seeking a career at the forefront of technological innovation or looking to position yourself in one of the most impactful sectors of the digital economy, machine learning represents an exceptional opportunity. The convergence of abundant data availability, computational power accessibility, advanced algorithmic development, and enterprise AI adoption has created perfect conditions for machine learning career success.