Data Scientist/Lead Quantitative Analyst
Join Guidepoint's newly-formed Data & Analytics group and help spearhead the development of our growing data offerings.
We are seeking a candidate that is looking to work with data of various sizes, structures and types to help build and expand our analytics-focused products. From MB of numeral data needing multi-variable statistical assessment to TB of text based data requiring machine learning and lexical indexing and analysis, you'll work with a range of exciting data. You will be required to employ (or quickly learn and find out how to employ) your own technologies to extract meaningful, statistically significant insights without technical guidance. Methodologies you develop and employ will set the foundation for future products and offerings. This role offers a high level of responsibility and the opportunity to build a market-leading business.
We have TB of interesting, proprietary data from incredible sources just waiting for the right person to dive in and help us build the most valuable products to deliver insights on The Street.
- Responsible for the strategic development, deployment and maintenance of methodologies that will help drive Data & Analytics product offerings including the application of various statistical modeling and time-series analysis techniques to build top-line, company specific metric predictions
- Ability to "roll-up sleeves" and directly work with messy and complex data but also feel comfortable delegating and guiding team of analysts
- Research and build core understanding of sector and company performance metrics and market controversies to qualitatively inform and interpret models
- Support growth and professional development of junior analysts
- Must be intellectually curious, self-directed, highly driven with an entrepreneurial mindset
- Must have a hunger for solving complex, difficult big data problems with a sense of urgency
- Must have advanced working knowledge of SQL, Java, C#, R, Matlab or other languages/technologies for performing complex data modeling and analysis
- Graduate or undergraduate degree(s) in qualitative field: CS, Math, Statistics, Engineering, etc.
- Familiarity with and ability to apply the following concepts to solve data problems:
- Natural Language Processing: the interactions between computers and humans;
- Machine learning: using computers to improve as well as develop algorithms;
- Conceptual modelling: to be able to share and articulate modelling;
- Statistical analysis: to understand and work around possible limitations in models;
- Predictive modelling: most of the big data problems are towards being able to predict future outcomes;
- Hypothesis testing: being able to develop hypothesis and test them with careful experiments.
- Broad understanding of or interest in current controversies on Wall Street
- Excellent communication skills and ability to build and lead a team of analysts
- Explain complex data analysis techniques and technologies to clients
- Strong desire to be a part of a high-growth, rapidly evolving business
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