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 Ph.D., 1-4 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 New York City Headquarters, this is a great opportunity for a fairly recent Ph.D. 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 modeling, 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 data sets 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 geospatial 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 a deep understanding of the fundamentals of research design and causal inference.
- Solid fundamentals of 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 1-4 years of professional experience as a Data Scientist OR Relevant Masters and 3+ years of professional experience as a Data Scientist. Relevant = Ph.D. or 2 yr Masters Program in any field with a strong 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.