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About the role
Job_Description":" 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, youre 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 harderLets 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 doesnt need hand holding What Youll 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 companys 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 - 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 ","