TITLE: SENIOR / DATA SCIENTIST
REPORTS TO: Head of Data Science
GROUP: Innovation R&D Group
FOCUS: Experimentation and Development of Predictive Machine Learning Layer
LOCATION: New York City
IDEAL CANDIDATE: Quantitative PhD, 1-2 years of professional experience as a Data Scientist + skills listed below. Masters graduates with 2+ years experience in the field will also be considered.
POSITION / CLIENT OVERVIEW:
Based in the the New York City Headquarters, this is a great opportunity for a recent PhD or Masters grad to transition into a Data Science Innovation R&D Group to experiment and develop out the predictive machine learning layer at well-funded (Series B) startup in the Location-based Intelligence (Data & Analytics) space. You will work with massive datasets using the latest tools and techniques to arrive at innovative solutions to some of the biggest problems in the marketing and advertising industry (including: Omni-channel attribution measurement, how to best use Geo-location data, and user privacy).
To be 100% clear this role is for R&D, and not to help rush products out the door.
- Apply state-of-the-art machine learning methods and paradigms to model complex business problems using location-based data.
- Use statistics and operations research methodologies to discover insights and identify business opportunities for inside and outside clients.
- Build smarter products using location-based and time-series data using a multi- methodological mindset (traditional statistical modelling, machine learning, deep learning, etc.).
- Implement distributed prototypes of any machine- or deep-learning product or enhancement.
- Coordinate with the in-house engineering team to develop efficient and powerful machine-learning layers on top of existing systems.
- Audit data-generation procedures and pipelines to guarantee congruent and reliable data.
- Design and develop creative prototypes to enhance the existing client-facing products.
- Prototype and test new products and enhancements using the existing data.
- Think creatively about which new data sources could be added, as well as ways of linking disparate datasets using advanced methodologies.
- Guarantee that the data science products conform to peer-reviewed publishable standards of quality.
- Stay updated in the most recent relevant machine learning, geospatial technologies, and deep learning advances in the respective fields.
- Identify what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as curation and geo-spatial information.
- Propose creative ideas, experiment, fail or succeed, and move to production if approved.
- Conduct advanced data analysis and highly complex designs algorithms.
- Make strategic recommendations on data collection, integration and retention requirements incorporating business best practices.
- Initial data exploration, prototyping and deployment of data-driven production code.
- Effectively communicate your findings to the business by exposing assumptions and validation work in a way that can be easily understood by business counterparts.
- Apply advanced statistical and predictive modeling techniques to build, maintain, and improve decision systems.
- Our team focuses on delivering both research and results in a collaborative and supportive environment.
- MUST HAVE deep understanding of the fundamentals of research design and causal inference.
- Solid fundamentals on statistical tests, distributions and model assumptions.
- Solid familiarity applying Machine Learning algorithms to various problems
- Solid fundamentals of advanced linear algebra and calculus. Deep Learning is a nice to have.
- Experience with geospatial concepts, data, pipelines, methods and platforms.
- Strong familiarity with EC2, S3, cluster management.
- Strong programming skills (Python, PySpark/Spark, R). Scala is a nice to have.
- Solid fundamentals in scalability (distributed systems), in order to work with Data Engineers.
- Ability to work with, and maintain a professional code base (git)
- Proficiency in forecasting/predictive analytics,and optimization algorithms
- Min Requirement:Relevant Ph.D. and 1+ years of professional experience as a Data Scientist OR Relevant Masters and 3+ years of profession experience as a Data Scientist. Relevant = PhD or 2 yr Masters Program in any field with string quantitative component.
- Advanced coursework in statistics, machine learning, linear algebra.
- Hiring manager prefers candidates that use Github
- Base Salary ~$140K Base Salary + 15% Bonus
- Amazing Benefits: 5 Weeks of Vacation, 5% 401K Matching, Excellent Health Care Ins., Stock Options, etc.)
Note: H1B transfer is possible if you have at least 3 years of eligibility remaining and start date will not be delayed significantly.