Minimum 4 years of experience in Machine Learning or Data Engineering roles., BSc/MSc in a Scientific or Quantitative field., Strong proficiency in Python and SQL, with experience in data processing libraries like Polars/Pandas and sklearn., Familiarity with Kubernetes and cloud environments, along with Kafka producer experience..
Key responsabilities:
Develop and implement applications that achieve measurable market impact.
Build and optimize real-time and batch pricing algorithms.
Collaborate within a multidisciplinary team of engineers and data scientists.
Engage in deployment to Kubernetes environments and ensure efficient data processing.
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TheoremOne (now Formula.Monks) is an innovation and engineering company that advises clients on product strategy, engineering, design, and culture, then partners with them to build and launch technology-driven solutions to their most complex problems. TheoremOne is chosen by clients when results matter most — becoming the agent of change, and driving a transformation that involves not only technology, but also people, process and leadership. Founded in 2007, and headquartered in Los Angeles, Theorem’s global team of engineers, designers, technologists, researchers, strategists, and advisors, has deep expertise across a broad variety of industries including consumer electronics, automotive, manufacturing, supply chain, healthcare, finance, and entertainment. Learn more at www.theoremone.co
Formula.Monks, part of Media.Monks and S4 Capital, is a global consulting firm mastering AI-powered transformations for the Fortune 100. We combine long-term strategic thinking, deep enterprise experience, and a human-centered approach to help clients transform business processes and dominate their industries.
About the Role
As a Data Product Engineer, you will play a critical role in enhancing our machine learning capabilities and data-driven decision-making processes. You will work on impactful projects across multiple asset classes and collaborate within a multidisciplinary team to develop innovative applications and real-time pricing algorithms.
Responsibilities
Develop and implement applications that achieve measurable market impact
Build and optimize real-time and batch pricing algorithms
Collaborate within a multidisciplinary team of engineers and data scientists
Engage in deployment to Kubernetes environments and integration with existing data systems
Ensure efficient data processing leveraging Python libraries (Polars/Pandas, numpy, sklearn)
Work with SQL to design, query, and manage databases
Produce and consume events from Kafka for data streaming
Other duties as assigned
Qualifications & Skills
Minimum 4 years of experience in Machine Learning or Data Engineering roles
BSc/MSc in a Scientific or Quantitative field
Strong proficiency in Data/Machine Learning, Python, and SQL
Experience with Linux environments, including Bash scripting and basic network tools (SSH, SCP, FTP)
Familiarity deploying to Kubernetes and working in cloud environments
Kafka producer experience
Collaborative mindset, business-focused attitude, and ability to meet tight deadlines
Ability to read and edit others' code, ensuring quality and clarity
Nice to have:
Experience working across multiple asset classes
Knowledge of asset classes such as ETFs, Fixed Income, Equities, or FX is preferred
Unsure if your skills meet all of our requirements?
Apply anyway! We would love to learn more about you and find out about how your skills could add value. At Formula.Monks, we value open communication and feedback. We believe that diversity of identity, perspective, and experience makes us stronger; we would love to hear your perspective too!
Formula.Monks is an Equal Opportunity Employer; employment with Formula is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, marital status, mental or physical disability or any other legally protected status
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