We are looking to hire incredible Data Scientists interested in working with a US Startup. If you are truly passionate about designing and building machine learning solutions using python, you\u2019re looking for a job where you can work from anywhere- and we mean anywhere and are excited about gaining experience in a Startup, then this is the position for you. Be it your next vacation spot or a farm out in the country, if you have working internet, you can work remotely from your chosen location. No long commutes or rushing to in-person meetings. Ready to work hard and play harder? Let\u2019s work together.
[ Note: As part of the application process, candidates must complete the pre-screening behavioral assessment form. Without it, we will not consider candid ates for this position. ]
Requirements
- Pre-final year student in Statistics/Math, Computer Science, Finance/Economics, or related quantitative fields (Ph.D. candidates encouraged to apply)
- Experience using ML libraries, such as Scikit-learn, caret, NLTK or spark MLlib
- Excellent Software skills (proficiency in Python - Data Science stack)
- Build statistical and ML models to evaluate the historical performance and define predictive and prescriptive solutions
- Data Engineering experience/coursework and ability to integrate multiple data sources
- Has in depth working knowledge of SQL, relational databases, and a solid foundation in MS-Excel
- Experience using data visualization tools such Power BI, Tableau, etc.
- Comfortable with UNIX Operating System
- Knowledge of Docker and Git
- Strong analytical, design, problem-solving, and troubleshooting/debugging skills
- Ability to work independently in a home office and doesn\u2019t need hand holding
What You\u2019ll Do, But Not Limited To:
- Under the general direction of senior researchers, conduct empirical research using public and proprietary data
- Data gathering, data cleaning, building data models, and maintaining datasets
- Complete data preparation, data testing using Python (ETL), and a big part of day-to-day function
- Develop dashboards, charts, and visual aids to support decision making
- Utilize statistical techniques to help develop analytic insights, sound hypotheses, and informed recommendations
- Conduct ad hoc quantitative analyses, modeling, or programming using Python and SQL
- Diagnosing and resolving issues in production
- Enhancing and developing all aspects of the company\u2019s technology suite by collaborating with development teams to determine application requirements
- Assessing and prioritizing client feature requests
Who You Are:
- Highly Quantitative - your skills are the envy of all your friends
- Reliable, Independent, and able to wear multiple hats
- Honest - we hold transparency with high regard
- Team Player - likes collaborating and working as a team
- Communicative - Strong verbal and written communication skills
- Self-Starter - able to take ownership of projects and identify what needs to be done
- Builder - You are passionate about delivering better products/experiences to our customers and have a deep sense of ownership for your work
- Experimental - You love trying new things, new tools, techniques and approaches even if you fail sometimes
Nice To Have:
- Pursuing/Completed Ph.D./Masters in Finance, Economics or Business
- Have built quantitative models either in course work or in other internships is a plus
- Intellectually curious and eager to learn about Finance (Investments and Corporate Finance)
- Prior internship experience in Financial Services
Benefits
- Remote First Company - 100% remote to work with your schedule
- Flexible Hours
- Competitive Stipend/Salary
Note:
- Zero-tolerance policy for plagiarism on the screening test. Any indication that the submission contains a solution generated by AI platforms like ChatGPT will lead to immediate disqualification.
- Please only submit your assignment as a zip attachment in an email. Any other forms of submission will be auto-rejected
- Preference will be given to candidates from top schools at Pune University, Mumbai University, NIT, IISER, TIFR, IIT, ISI or a top schools in USA/UK