Data Engineer
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3 - 8 yrs
₹30L - ₹60L / yr
Mumbai
Skills
PythonInvestment banking
Data Engineer - Python
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.
Your future role within QRT
- Use Python web frameworks such as Dash or Streamlit to make latency data accessible to end users.
- Leverage OpenAI API to analyse and generate insights by using latency data and provide visualization interface to end users.
- Improve the Latency Data API to provide seamless access to latency data for end users, including researchers, support, and other teams within QRT.
- Optimize and fine-tune Large Language Models (LLMs) for use cases in natural language understanding, data processing, and predictive modelling.
Your present skillset
- 4+ years' experience in a related field
- Advanced Python and OpenAI API proficiency.
- Good with LLM Concepts.
- Experience with large data sets, visualizations, and reports.
- High standards in code quality and development practices.
- Proficiency in managing structured/unstructured data.
- Expertise in scalable data systems.
- Strong AI/ML skills for pattern and anomaly detection.
- Experience with CI/CD processes and DevOps.
- Experience in the financial/trading sector.
- Familiarity with latency-sensitive systems and performance optimization
QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.
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