Data Science Intern

Hashstack
Hashstack is on a mission to build an ecosystem of trustless, borderless autonomous financial products that serve the needs of millions of underserved around the world. Our product, Open protocol facilitates secure under-collateralized loans to the retail cryptocurrency market.

This is an onsite role in Bangalore, India.

Our Technology
We use NodeJs in the backend to monitor on-chain & off-chain processes. The client is built in ReactJs/Ant UI. Our APIs are served through GraphQL. We have a dual server set-up. Our infrastructure is deployed on AWS & GCP.

Requirements:

• Pursuing the final year of college or a Bachelor's degree in Computer Science, Mathematics, Statistics, or other analytical fields is mandatory.
• Previous Internship experience or work experience in applying Machine Learning, Statistics, text-mining, fintech analysis, information retrieval, information extraction, AI, deep learning, etc.
• Strong in-depth knowledge in different areas of data mining as well as reasonable programming and design skills to manipulate Big Data and build prototypes that work on massive datasets.
• Programming knowledge: Hands-on experience in python.
• Practical knowledge of ml tools - Panda, RNNs, Scikit-Learn.

Bonus points [Nice to have]

• Hobby projects/Hackathons to showcase your skillset
• First principles thinking
• Self starter

Scope of work

• Develop and refine models to predict on-chain user behavior and help prescribe actions to improve forecasting, and personalization.
• Transition proof of concept models into scalable personalized solutions for consumer-facing experiences
• Gain deep insight into user behavior and business impact; present findings to internal stakeholders.
• Support exploration of new technologies and analysis methods to identify growth/efficiency opportunities
• Interacts with product, growth, and tech teams to identify questions and issues for data analysis and experiments.

What to expect

We are results-driven. We get things done. We work hard. When we fail, we learn fast, & pick ourselves up.

• Opportunity to work on significant problems.
• Fast-moving, challenging & complex business problems.
• Competitive salary & flexible hours.
• Meritocracy culture.