Client: Global Financial Investment Manager
Location: New York City (2-3 Days a week / Remote to start)
Focus: Redefine the way traders, portfolio managers, and analysts serve our investor client base using the latest techniques in ML, DL, NLP, and A.I.
Target Compensation: ~$250K-300K All-in
Sponsorship: Not Available
About the Role: The VP, Senor Data Scientist position has been established to provide digital solutions and leading analytical expertise on new and novel approaches to problems in the investments domain. Including working with Portfolio Managers to improve investment selection, asset allocation, and other aspects of the business.
You’ll work with top talent across our business to create groundbreaking, next-generation applications for n-tier cloud architectures. You’ll be involved, hands-on, through the entire development cycle.
You'll get to work on novel solutions, learn and grow in the collaborative culture that encourages every member of our team to bring their point of view to the table.
Core Attributes:
- The ideal candidate will have strong collaboration skills as well as possess statistical, mathematical, predictive modeling, and business strategy skills to build the algorithms necessary to ask the right questions and find the right answers.
- The incumbent will be expected to develop attribution, segmentation, and predictive models to support our investment research process. It is expected this will be accomplished through pilot, test, and learn delivery practice to support a wide range of deliverables with our business partners.
- Equally important to possessing strong technical skills, the ideal candidate will be a strong communicator able to communicate their findings, orally and visually. They need to understand how the products are developed and even more important, as big data touches the privacy of consumers, they need to have a set of ethical responsibilities.
- Exceptional technology skills; recognized by your peers as an expert in your domain.
- A proponent of strong collaborative software engineering techniques and methods: agile development, continuous integration, code review or pairing, unit testing, refactoring, and related approaches.
Responsibilities:
Extracts knowledge and insights from high volume, high dimensional data in order to investigate complex business problems through a range of data preparation, modeling, analysis, and/or visualization techniques, including predictive analysis, business intelligence, pattern recognition, operational effectiveness, and/or economic forecasting.
- Drives adoption of Data Science techniques within investments domain
- Represent the data science community at internal and external forums
- Stays abreast of industry trends, driving leading-edge changes and championing firm adoption of new technologies
- Operates as a hands-on technologist, delivers within a team as an individual data scientist
- Leads the firm’s most ambitious, business-critical and/or complex Data Science projects
- Maintains a broad professional network both internally and externally and leverages it skillfully to achieve results
Required Technical Experience:
- Masters in a relevant quantitative field
- 4+ years as a professional Data Scientist
- A thorough understanding of applied statistics including sampling approaches, causal modeling, time series analysis, and data mining techniques
- Experience in working with large structured and unstructured data sets
- Fluency in the languages of data manipulation (e.g. SQL) and statistical analysis (e.g. R or Python/NumPy), with the ability to code a plus: e.g. Java, Ruby, Clojure, Matlab, Pig or SQL
- Understanding of Hadoop, Hive, and/or MapReduce
- Natural Language Processing
- Machine Learning
- Conceptual modeling
- Statistical analysis & Predictive modeling
- Hypothesis testing
Compensation: ~$175K -$200K base + ~$100 Bonus Target (Potentially Able to Guarantee First Year Compensation)
TO APPLY: Contact [email protected]