Remote Data Product Engineer

Description:

• As a Data Product Engineer, you will play a critical role in enhancing 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 include developing and implementing applications that achieve measurable market impact, building and optimizing real-time and batch pricing algorithms, and engaging in deployment to Kubernetes environments.
• You will ensure efficient data processing leveraging Python libraries such as Polars/Pandas, numpy, and sklearn.
• The role involves working with SQL to design, query, and manage databases, as well as producing and consuming events from Kafka for data streaming.
• Other duties may be assigned as needed.

Requirements:

• A minimum of 4 years of experience in Machine Learning or Data Engineering roles is required.
• A BSc/MSc in a Scientific or Quantitative field is necessary.
• Strong proficiency in Data/Machine Learning, Python, and SQL is essential.
• Experience with Linux environments, including Bash scripting and basic network tools (SSH, SCP, FTP), is required.
• Extensive experience with the Data Science stack, specifically Python (Polars/Pandas), numpy, and sklearn, is necessary.
• Familiarity with deploying to Kubernetes and working in cloud environments is important.
• Experience as a Kafka producer is required.
• A collaborative mindset, business-focused attitude, and the ability to meet tight deadlines are essential.
• The ability to read and edit others' code, ensuring quality and clarity, is necessary.

Benefits:

• Formula.Monks values open communication and feedback, fostering a culture of collaboration and innovation.
• The company is an Equal Opportunity Employer, ensuring that employment is governed on the basis of merit, competence, and qualifications.
• Formula.Monks encourages applicants to apply even if they are unsure about meeting all requirements, promoting a diverse and inclusive workplace.