A client in SoHo is seeking to bring on a Data Scientist:
Problems you will solve: understanding data, identifying patterns, quantifying the impact of ML / NLP models and designing data visualizations
As one of the founding members of a small, multi-disciplinary team of technologists, designers and product managers, you'll have the freedom to make key product decisions without much oversight, and the tools and resources to build and ship ideas quickly. You'll be a part of a startup-like environment, with the opportunity to have more control and leadership; in a company with thousands of existing customers.
Who you are
- You want to use your statistical, scientific, and engineering training to craft and deploy models to transform one of the most entrenched industries.
- You paint with plots and your models don't keep secrets.
- Image recognition is no longer an innovation to you, instead it is a routine task.
- NLP isn't a foreign acronym and you've gone from strings to whiskers.
- You sail smooth in Python and always have sklearn, tensorflow, keras and pytorch on deck.
- K-means more than a curt text and Logit and Probit are not Hobbit characters.
- You have experience with relational databases such as PostgreSQL, Oracle or SQL Server, and maybe even Hadoop, Hive, Spark or Redshift.
- You strive to learn the newest and greatest techniques where BERT/ELMo are not just Sesame Street© characters.
What you'll own
- The foundation for advanced analytics at a global company.
- The roadmap of projects you'll work on that tie directly to business goals and objectives.
- Manage the entire lifecycle of data projects from strategic planning to tactical activities (data collection, cleanup, analysis, model implementation).
- Sourcing new data for a firm that rarely scrapes, pulls or pushes.
- Facilitate communication throughout the development process between executive stakeholders, your users and technical teams.
- Coordinate and build strong working relations with various internal stakeholder groups, including IT, engineering, and legal.
- Degree in computer science, engineering, mathematics, statistics, data science or a related technical field, or equivalent practical experience.
- 3 years of work experience in data science or related field.
- Experience with statistical modeling using R, Python, or similar statistical languages.
- In depth knowledge of advanced models such as generalized linear models, penalized regression models, tree based models and neural networks
- Proven track record building business-practical models and implementing them into production.
- Familiarity with Pandas, Numpy, Scikit-learn, Keras, Tensorflow, Pytorch
- Experience with data architecture and management (PostgreSQL, Hadoop, Oracle, Hive, Spark, Redshift and/or SQL Server)
Generalized Linear Model