Trade Monitoring Analyst Jobs

We are seeking an experienced Trading Operations Specialist to assist the company in executing trading strategies and ensuring the effective risk management of trading activities. This role involves overseeing pre-trade, live, and post-trade monitoring, stress testing algorithms, implementing kill functionality, monitoring market abuse, and raising red flags to senior management and compliance as necessary What You’ll Be Doing: Have access to and oversee the implementation of the kill switch to manage and mitigate trading risks promptly Lead a first-line team responsible for owning and managing trading risks, including stress testing algorithms and monitoring trade executions Review and approve new algorithms, parameters, and risk limits before they go live Monitor trades in real-time and review open positions to make informed decisions and adjustments as needed Raise red flags to the CEO, compliance team, and relevant stakeholders for immediate action and resolution Liaise with regulators on compliance matters where necessary Collaborate with the trading desk to ensure smooth and efficient trading operations while adhering to risk management protocols What We Look For In You: Bachelor's degree in Finance, Economics, Mathematics, or a related field 5+ years of proven experience in trading operations, risk management, and market surveillance within the financial industry Strong understanding of trading strategies, algorithms, risk metrics, and market dynamics Excellent analytical skills and the ability to assess and manage trading risks in real-time Proficiency in using trading platforms, automated monitoring tools, and risk management software Effective communication and decision-making skills to lead and collaborate Why Should You Join Our Team? Join an international team of highly qualified professionals Cutting-edge hardware and technology Onsite work at our Malta office (relocation to Malta is required) 40 paid days off Competitive salary

We are seeking an experienced, analytical, and highly structured professional to join our Group Treasury team in the Middle Office. This role is central to reporting and compliances related to Treasury’s risk management activities. The selected candidate will ensure stringent risk management, system implementations, valuation precision, internal and external compliances related to risk management, and strategic risk and performance reporting. You will play a vital role in analyzing and controlling the risk of treasury dealings, monitoring trade execution, keeping and active and analytical eye on daily P&L and Mark-to-Market (MTM) calculations as well as the positions run by the traders, ensure zero exceptions by traders and timely rectification / ratifications of the same if any. Source: Adani Group | Job ID: 53803

Junior Data Scientist The Wiley Edge banking team is currently seeking a Data Scientist to work across the Front Office Trading, Risk & Regulatory Compliance Trade Analytics group, using Machine Learning and Data Analytics techniques to design and develop complex data models for client and trading analytics across their Fixed Income and FX offerings. You will be supporting the transformation from traditional controls monitoring to “on-screen” data driven monitoring and analytical solutions. Tools: Python (pandas, numpy) Machine Learning Algorithms / Natural Language Processing (NLP) AI / Robotics Predictive Analysis Good grasp of ML Algorithms Starting Salary: CA$85,000 per annum Junior Data Scientist

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. ROLE Dynamically managing portfolio risk by evaluating historical and real-time strategy performance. Overseeing automated trade execution and monitoring transaction costs. Supervising a small team of researchers and developers on a daily basis. Designing, researching, and managing sophisticated investment strategies by creating and engineering advance quantitative financial computer modeling systems to aid in analysis and research. Performing research to acquire historical and production data sources needed to build investment models. Designing and developing quantitative mathematical algorithms to link the diverse data sets from various providers. Engineering investment models that will make the buy and sell recommendations for the portfolios using advanced quantitative mathematic statistics and investment theory to design and program strategies that explicitly forecast risk, return, and trading costs. Using quantitative models to value securities. Conducting ongoing, cutting-edge quantitative research and analysis to enhance existing strategies and to expand into new markets. Developing aspects of successful statistical models, focusing on forecasting and optimization. Expanding trading universe and volume and expanding to other exchanges and products. REQUIREMENTS Advance degree (Masters or Ph.D.) in a computational or analytical field. Minimum of 10 years’ experience developing, researching or implementing quantitative models for equities, futures and/or FX. Hands on experience with all aspects of the research process, including methodology section, data collection and analysis, testing,

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. ROLE Dynamically managing portfolio risk by evaluating historical and real-time strategy performance. Overseeing automated trade execution and monitoring transaction costs. Supervising a small team of researchers and developers on a daily basis. Designing, researching, and managing sophisticated investment strategies by creating and engineering advance quantitative financial computer modeling systems to aid in analysis and research. Performing research to acquire historical and production data sources needed to build investment models. Designing and developing quantitative mathematical algorithms to link the diverse data sets from various providers. Engineering investment models that will make the buy and sell recommendations for the portfolios using advanced quantitative mathematic statistics and investment theory to design and program strategies that explicitly forecast risk, return, and trading costs. Using quantitative models to value securities. Conducting ongoing, cutting-edge quantitative research and analysis to enhance existing strategies and to expand into new markets. Developing aspects of successful statistical models, focusing on forecasting and optimization. Expanding trading universe and volume and expanding to other exchanges and products. REQUIREMENTS Advance degree (Masters or Ph.D.) in a computational or analytical field. Minimum of 10 years’ experience developing, researching or implementing quantitative models for equities, futures and/or FX. Hands on experience with all aspects of the research process, including methodology section, data collection and analysis, testing,

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. ROLE Dynamically managing portfolio risk by evaluating historical and real-time strategy performance. Overseeing automated trade execution and monitoring transaction costs. Supervising a small team of researchers and developers on a daily basis. Designing, researching, and managing sophisticated investment strategies by creating and engineering advance quantitative financial computer modeling systems to aid in analysis and research. Performing research to acquire historical and production data sources needed to build investment models. Designing and developing quantitative mathematical algorithms to link the diverse data sets from various providers. Engineering investment models that will make the buy and sell recommendations for the portfolios using advanced quantitative mathematic statistics and investment theory to design and program strategies that explicitly forecast risk, return, and trading costs. Using quantitative models to value securities. Conducting ongoing, cutting-edge quantitative research and analysis to enhance existing strategies and to expand into new markets. Developing aspects of successful statistical models, focusing on forecasting and optimization. Expanding trading universe and volume and expanding to other exchanges and products. REQUIREMENTS Advance degree (Masters or Ph.D.) in a computational or analytical field. Minimum of 10 years’ experience developing, researching or implementing quantitative models for equities, futures and/or FX. Hands on experience with all aspects of the research process, including methodology section, data collection and analysis, testing,

NK Securities Research is a leading financial firm that leverages cutting edge technology and sophisticated algorithms to trade the financial markets. Founded in 2011, we have gained invaluable experience in the field of High Frequency Trading across different asset classes. We are seeking a Network Infrastructure Manager to lead our network operations, ensure setup, maintenance, reliability, and optimize performance to support our trading activities. Key Responsibilities: As a Network Infrastructure Manager, you will be responsible for designing, implementing, and managing the firm’s network infrastructure to ensure high availability, low latency, and security. You will collaborate with trading, systems, and development teams to meet the demanding requirements of algorithmic trading and maintain seamless exchange connectivity. Design and implement network infrastructure in colocation for low latency exchange connectivity Design and implement network infrastructure for inter and intra data centres Develop scalable network architectures to accommodate growing business requirements Optimize network performance for local, wide-area, and data center networks. Oversee daily network operations, ensuring 24/7 network availability and minimal downtime. Manage network related hardware such as switches, routers, and firewalls across multiple data centers. Lead incident response for network issues, identifying root causes and implementing solutions. Develop and maintain tools for real-time network monitoring and performance analysis. Optimize configurations for minimal packet loss, latency, throughput and jitter. Evaluate and implement new technologies to improve network efficiency and reliability. Ensure network security by managing firewalls, VPNs, and intrusion detection systems. Collaborate with compliance teams to ensure adherence to regulatory requirements. Implement best practices for securing sensitive trading data and infrastructure. Work closely with trading, develop

Support Analyst - Risk and Trading Large investment bank requires an Application Support Analyst to join their Front Office facing Trading and Risk group providing 1st and 2nd line support and enhancement to their electronically traded products and associated infrastructure solutions for trading execution. Candidates will be responsible for facing off to traders, risk managers and external clients providing Application Support Analyst expertise, increasing of systems performance, automation, infrastructure systems deployment, extensions and analysis of the implementation and integration requirements for the global trading system. Candidates will be expected to hold some understanding of production environments across large scale distributed global systems gained from either an Investment Bank, Software House, Global Telco, FinTech, Hedge Fund or comparable environment utilizing Unix / Linux. Full detailed spec available. Suitable skills: Production Support Analyst Large Scale Systems Application Support CI/CD Database manipulation in SQL Unix/Linux Scripting Python Scripting skills Application Monitoring Some desire to learn / appreciation of Devops and automation tools Support Analyst - Risk and Trading

About the Team At Trendyol Finance, we drive financial clarity, sustainability, and smart decision-making at every level of the business. As a strategic partner to commercial teams, we bridge data with action—ensuring efficiency, compliance, and long-term value creation. From budgeting to forecasting, we turn numbers into insights that shape Trendyol’s growth journey in a fast-moving ecosystem. About the Role We are seeking analytical, process-oriented and proactive Fraud Process & Analytics Professionals to join our Fraud team. This role sits at the intersection of fraud domain knowledge, data analysis, process design and project delivery. You will identify fraud and abuse risks, translate business problems into analytical questions, use data to quantify root causes and impact, design scalable controls and rulesets, and drive improvements together with Product, Data, Tech, Operations and Business teams. The role is not limited to reviewing individual cases; the main focus is to turn recurring fraud problems into measurable, scalable and sustainable solutions. Your Main Responsibilities Own and improve fraud-related processes end-to-end by identifying control gaps, bottlenecks, manual steps and potential abuse points, and drive scalable improvements through automation, product changes or operational redesign. Analyze customer, seller, order, payment and behavioral data using SQL / BigQuery to identify fraud patterns, anomalies, root causes and emerging risk signals; structure ambiguous problems into clear hypotheses, populations and success metrics. Quantify the financial, operational and customer/seller experience impact of fraud problems, prioritize initiatives accordingly, and translate analytical findings into actionable recommendations. Design and improve fraud rulesets, risk indicators, thresholds, controls and monitoring frameworks, considering false positive / false negative trade-offs and overall control effectiveness.

Given heightened expectations from regulators and a goal to build a strong and consistent global control environment, Citi continues to enhance its business governance framework and has created the Enterprise Data group. Enterprise Data is a critical component of Citi’s first line of defense for wholesale and counterparty credit risk management and works with Independent Risk teams to ensure best-in-class risk and controls, as well as client responsiveness. Key responsibilities of the group include credit analysis, documentation, risk identification, exposure monitoring and stress testing. Enterprise Data coordinates with credit management groups across institutional client businesses to ensure full alignment on business and regulatory goals, as well as consistency and best practices. The Counterparty Credit Risk (CCR) project execution team within Enterprise Data is responsible for building tools to: Provide in-depth quantitative or qualitative analysis to solve business problems and develop new, innovative solutions Build tools to help measure, monitor and control counterparty risk for institutional clients and Portfolios and businesses, with a focus on counter-party and collateral risk to ensure the risks are being properly measured and controlled in accordance with the Firm’s risk policies. Responsibilities: As a Product Developer working in CCR project team, individual will be expected to Lead strategic BAU and Regulatory projects primarily impacting Counterparty Credit Risk exposure measures for traded product markets business Develop and enhance tools for the measurement, monitoring and reporting of counterparty exposure including Stress testing - Net Stressed Exposure (NSE), Potential Future Exposure (PFE), Settlement Risk, Intraday risk and participate in project management of strategic risk infrastructure development.</

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role The Events Analytics Platform (EAP) team is responsible for the infrastructure that powers all of Sentry's time-series data and searching capabilities across billions of events with sub-second latency. We started this initiative by building Snuba, the primary storage and query service for Sentry's event data powered by ClickHouse, and we are now focused on unlocking deeper visibility and reporting across the terabytes of event data our users generate. As a Senior Software Engineer, you will lead efforts to push the boundaries of data visibility at Sentry. You will do this by expanding the capabilities of our search infrastructure, building new capabilities on top of our state-of-the-art storage layer and increasing the performance and integrity of Sentry’s core data services. You will also help shape Infrastructure's technical direction at Sentry and collaborate with Product and other Engineering teams to turn that vision into a reality. If you want to solve the hard problems that come with scaling event data into the petabyte range, this could be the job for you. In this role you will: Expand EAP's ability to deliver data at world-class speed and reliability. Architect and automate services and systems to scale reliably under growing demand. Make architectural trade-offs that balance product requirements with engineering constraints. Maintain and grow the team's code quality initiatives by regularly reviewing code and contributing to design decisions. Lead design and discussions around deliverables the team is working towards. Improve the maintainability and developer experience of the codebases EAP owns. Exa

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role The Events Analytics Platform (EAP) team is responsible for the infrastructure that powers all of Sentry's time-series data and searching capabilities across billions of events with sub-second latency. We started this initiative by building Snuba, the primary storage and query service for Sentry's event data powered by ClickHouse, and we are now focused on unlocking deeper visibility and reporting across the terabytes of event data our users generate. As a Senior Software Engineer, you will lead efforts to push the boundaries of data visibility at Sentry. You will do this by expanding the capabilities of our search infrastructure, building new capabilities on top of our state-of-the-art storage layer and increasing the performance and integrity of Sentry’s core data services. You will also help shape Infrastructure's technical direction at Sentry and collaborate with Product and other Engineering teams to turn that vision into a reality. If you want to solve the hard problems that come with scaling event data into the petabyte range, this could be the job for you. In this role you will: Expand EAP's ability to deliver data at world-class speed and reliability. Architect and automate services and systems to scale reliably under growing demand. Make architectural trade-offs that balance product requirements with engineering constraints. Maintain and grow the team's code quality initiatives by regularly reviewing code and contributing to design decisions. Lead design and discussions around deliverables the team is working towards. Improve the maintainability and developer experience of the codebases EAP owns. Exa

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

Role: Application Reliability Engineer Location: Gurgaon Who we are Graviton Research Capital is a privately funded quantitative trading firm striving for excellence in financial markets research. We trade across a multitude of asset classes and trading venues using a diverse range of concepts, from time series analysis and stochastic models to machine learning and statistical inference. We analyse terabytes of data to identify pricing anomalies and drive innovation in financial markets. Key Responsibilities and Deliverables The ideal candidate will possess a strong background in technical support, with a passion for problem-solving and a commitment to excellence. As an Application Reliability Engineer, you will be responsible for: Monitor production services and respond quickly to alerts, incidents, and outages to ensure smooth operation and minimal downtime. Monitor trading systems and infrastructure., Triage issues across trading support services, databases, and infra; escalate and coordinate with the right owners, and drive root-cause analysis and ensure fixes are implemented for long-term stability. Serve as the first line of defense for trading operations. Proactively identify, address recurring issues, and build automation to reduce manual intervention. Improve observability by enhancing monitoring, logging, and alerting systems. Develop and maintain operational runbooks and SLO/SLA metrics. Eligibility and Required Skills Possess a degree in a highly analytical field, such as Engineering, or Computer Science 2-5 years of experience in Python, Shell/Bash scripting. Experience with Linux and shell/bash online tools. Hands-on experience with databases (SQL, NoSQL) Strong problem-solving and analytical skills Excellent communication skills Ability to remain calm and analytical under production pressure Good to have: Familiarity with monitoring/alerting stacks (Prometheus, Grafana, ELK, etc.) Familiarity with distributed messaging (Kafka) and caching systems (Red

We are seeking a highly analytical and technical professional to spearhead the evolution of our trading infrastructure. This hybrid role combines the fast-paced execution of a Trading Operations Specialist, the analytical rigor of a Risk Manager, and the technical capabilities of an AI-focused Developer. The successful candidate will not only manage daily operational workflows and risk monitoring but will also lead the digital transformation of these functions. You will leverage Large Language Models (LLMs), machine learning, and advanced scripting to automate legacy manual processes, improve predictive risk modeling, and build real-time performance visualization tools and analyses. Key Responsibilities: 1. Trading Operations and Performance Analysis with AI Manage the end-to-end lifecycle of trades across multi-asset classes. Develop agentic AI workflows using Python (ML) and MLOps tools to automate manual operations and reconciliations Perform daily P&L attribution and explain variance by decomposing market moves, Greeks, and new activity. Leverage AI/ML frameworks (e.g., OpenAI API, LangChain, or local LLMs) to build intelligent agents for anomaly detection in trade data and automated commentary generation for P&L reports. Ensure data integrity across trading systems, middle-office platforms, and downstream finance ledgers. Use AI tools to build reporting and analyses on trading performance and perform adhoc business analytics 2. Risk Monitoring & Control Intelligent Risk Management: Develop real-time, AI-driven risk models that use machine learning to predict market volatility and alert the desk to emerging cross-market risks. Develop and maintain sophisticated risk reporting dashboards for the desk. Requirements & Qualifications: Experience: 3+ years in front-office operations, quant