SupraOracles is hiring a

Data Research Analyst

Remote

Who We Are

Supra is pioneering the future of information services in global markets. As an exciting, ambitious, and well-funded startup with unique technical capabilities, we aim to be a future leader in decentralized data. Our team includes professionals, academics, and advisors with experience from leading institutions such as Purdue University, University of Cambridge, University of Pennsylvania, Columbia University, and University of Oxford. Additionally, our industry experience includes prestigious companies like JPMorgan Chase & Co., Qualcomm, ConsenSys, and Binance. Based in Switzerland with a remote-first policy, our globally distributed team spans over 35 countries. We are dedicated to solving the Oracle Dilemma through innovative solutions in consensus mechanisms, real-time data services, decentralized finance (DeFi), and Layer 1 (L1) technologies.

Trust, kindness, honesty, and a commitment to ethical, decentralized technologies are the cornerstones of our culture.

 

What we're looking for

We are in search of a Data Research Analyst who will play a pivotal role in enhancing our data-driven decision-making processes. 

We thrive on trust and honesty. We believe in the positive and ethical impacts these cutting-edge technologies in a decentralized environment can make on the world. Your alignment and cultural fitment to these core values and beliefs are of considerable value to us.

Role 

  1. Statistical Analysis and Machine Learning: Conduct time series analysis, employ statistical methods and machine learning algorithms, and develop probabilistic models to predict trends, derive insights from large datasets, assess risks and detect anomalies in transaction data.
  2. Develop and Implement Optimal Control Strategies: Design and apply model predictive control (MPC) solutions using optimal control theory and state-space models to enhance decision-making for DeFi systems.
  3. Algorithm Development for Large-scale Optimisation: Leverage novel methods to solve optimisation problems, to enhance and maintain system performance.

 

Requirements

 

  1. Educational Background (Essential): A degree in Computer Science, Mathematics, Engineering, or demonstrated equivalent self-learning. Proficiency in differential equations, linear algebra, system dynamics, state-space modeling, and numerical methods, would be greatly appreciated.
  2. Statistical Analysis (Essential): Demonstrable knowledge of statistics, time series analysis, and probability theory. Understanding of statistical methods and modern machine learning algorithms for inference and prediction.
  3. Control Theory (Highly desirable): An understanding of optimal control theory, model predictive control (MPC), and control systems design. Practical experience in designing and implementing MPC solutions and optimal control strategies for dynamical systems. Expertise in constraint handling and optimisation under uncertainty. Profound knowledge of optimisation techniques, including linear, non-linear, and dynamic programming. Familiarity with relevant solvers and optimisation tools.
  4. Programming Proficiency (Essential): Advanced skills in object-oriented programming, especially in Python.
  5. Large Dataset Management (Highly Desirable): Capability to manage challenges associated with large datasets, focusing on time series and unstructured data.
  6. Debugging and Version Control (Desirable): Experience in code troubleshooting and debugging. Proficiency in using Git or similar version control tools.
  7. Database Management (Nice to have): Competence in SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB) database management and querying. Experience with database design for storing and querying data would be nice
  8. Blockchain Familiarity (Nice to have): Basic understanding of blockchain technology, smart contracts, and DeFi principles.
  9. Qualitative Skills (Essential): Inquisitive nature, with the ability to critically assess and question information. Independence and ownership, with the capability to manage complex tasks with minimal guidance. High sense of agency and adaptability, with the ability to think on first principles in new situations to solve problems effectively.

What's In It For You

Joining Supra means joining a fast-growing startup with a diverse and dynamic team. Every role is impactful, allowing you to engage in meaningful work that contributes to our success.

You will enjoy the flexibility of a fully remote environment with adaptable working hours, enabling you to work from anywhere globally.

  • Competitive Compensation: We offer competitive compensation packages aligned with market standards.
  • Work-Life Balance: Eligible team members have access to flexible paid time off, sick leave, and other time-off options, adjusted in line with local regulations.
  • National Holidays: We recognize national holidays specific to each team member’s country and provide paid leave in accordance with local guidelines.
  • Health Benefits: Comprehensive health coverage options, including medical, dental, and vision benefits, are available to full-time employees where applicable.

Getting Started with Supra

We believe in giving you the space to settle in. Your first month is about orientation and learning:

  • Engage with your team to understand our business, vision, mission, and strategic goals.
  • Enhance your skills to navigate the evolving DeFi landscape.
  • Absorb our core values and establish connections with your colleagues through one-on-one meetings.
  • Familiarize yourself with the tools and processes vital to our operations.
  • Analyze our product offerings and contribute to discussions that shape our future.

We're here to support your integration and ensure you have the resources you need!

Looking Ahead

Regular check-ins with your manager will help align your priorities with our team and company goals, setting you up for success. At Supra, you're not just joining a company but embarking on a journey to enhance blockchain technology with a team of exceptional individuals.

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