The Role

We are seeking an exceptionally talented individual to join our Cross-Asset Derivatives Risk Management team as a Risk Manager. This role will focus on risk management and portfolio oversight of the firm’s Equity Derivatives, Macro EM and Delta One strategies, which include Equity vol, Fixed Income, Index Rebalance & Special situations strategies amongst others.

What you’ll do 

As a Risk Manager, you will:

• Report to the Head of Cross-Asset Derivatives Risk and partner daily with Portfolio Managers, Strats, and developers to monitor portfolios and design solutions that reduce concentration and stress risks.
• Build, implement and validate models that power both risk management and the investment process.
• Partner with our Technology organisation to enhance data infrastructure, automate risk-limit monitoring and streamline raw-data ingestion.
• Work with Portfolio Managers, providing regular and ad-hoc analytics on strategy performance, risk profiles and tail-risk scenarios.
• Collaborate with strategy COO, fellow risk managers and tech teams to build and maintain the modelling, pricing and analytics toolkit that powers our multi-strategy platform.

What you’ll bring
What you need:

• A minimum of 5 years’ relevant experience in a PM-facing role
• Strong knowledge of equity derivatives and portfolio risk management
• Knowledge of quantitative finance including risk-neutral options pricing and cross-sectional factor models
• Experience analyzing and modeling large data sets
• Strong coding skills in one or more languages such as R, Python or C++
• Experience working with relational databases such as MySQL
• Strong communication skills

We’d love if you had:

• Direct experience in Macro, Delta one and Equity Derivatives Strategy

Who we are

Schonfeld is a global multi-manager hedge fund that strives to deliver industry-leading risk-adjusted returns for our investors. We leverage both internal and external portfolio manager teams around the world, seeking to capitalize on inefficiencies and opportunities within the markets. We draw from decades of experience and a significant investment in proprietary technology, infrastructure and risk analytics to invest across four main strategies: Quant, Tactical, Fundamental Equity and Discretionary Macro & Fixed Income.

Our Culture

At Schonfeld, we’ll invest in you. Attracting and retaining top talent is at the heart of what we do, because we believe that exceptional outcomes begin with exceptional people. We foster a culture where talent is empowered to continually learn, innovate and pursue ambitious goals. We are teamwork-oriented, collaborative and encourage ideas—at all levels—to be shared. As an organization committed to investing in our people, we provide learning and educational offerings and opportunities to make an impact. We encourage community through internal networks, external partnerships and service initiatives that promote inclusion and purpose beyond the firm’s walls.

#LI-DK1

About the team

The Careem Data Science team’s mission is to drive competitive value from data at scale through building AI models to optimize user experiences, decision-making, operational efficiencies, and lead the region’s AI ecosystem. As one of the tech leaders in this team, you will be at the forefront of fulfilling this mission. You will be working with the top data science talent of the region, while innovating on our user experience using GenAI.

What you'll do

• Be part of a 0-1 AI transformation for the Careem app from a personalization perspective.
• Build a long-term vision on how we can rethink our customer acquisition and engagement strategies, leveraging data in our decision-making.
• Drive exploratory analysis to understand the ecosystem, user behavior, and identify new levers to help move metrics and build models of user behaviors for analysis and product enhancements.
• Shape and influence data/ML models and instrumentation to optimize the product experience and generate insights on new areas of opportunity and new products.
• Provide product leadership by sharing data-based recommendations to communicate the state of the business, the root cause of change in metrics, and experimentation results, influencing product and business decisions
• Implement scalable machine learning algorithms that will be used in production on big data.
• Embark on exploratory data analysis projects to achieve a better understanding of phenomena as well as to discover untapped areas of growth and optimization. 
• Answer complex analytic questions from big data sets to help Careem shape its products and services in a better way.
• Help define and track the appropriate key metrics for specific projects. 
• Design and run randomized controlled experiments, analyze the resulting data, and communicate results with other teams.
• You will always challenge the status quo and continually investigate new data processing technologies and seek to ensure that we follow the industry best practices.
• Build and deploy retrieval augmented generation systems and other applications of large language models.

What you'll need

• 7-9 years of experience in data mining, predictive modeling, time series analysis, machine learning, Big Data methodologies, and transformation and cleaning of both structured and unstructured data.
• Advanced degree in a quantitative discipline such as Physics, Statistics, Mathematics, Engineering or Computer Science.
• Solid experience with Deep Learning Techniques (e.g, attention, retrieval models, etc)
• 1-2 years of industrial experience in personalization, recommendation or search is a MUST. Preferably working in a product-driven company.
• Strong problem-solving and coding skills.
• Solid knowledge of AB testing, classic ML, and DL
• Solid understanding of recommendations, ranking, and retrieval. 
• Proficiency and demonstrated experience in: Python, SQL, Spark, Hive.
• Demonstrated experience with database technologies (e.g. , Hadoop, BigQuery, Amazon EMR, Hive, Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL).
• Demonstrated experience with business intelligence and visualization tools (Tableau, MicroStrategy, ChartIO, Qlik) along with geospatial data processing skill, is a plus.