As a Data Scientist at Noodle.ai, you will collaborate with our Enterprise Services team,Software Engineers, Designers, and industry-specific experts from our customers. You willvbuild a deep understanding of the business problems our customers are tackling and then develop, test, and deploy advanced machine learning algorithms. As we grow, you will also develop reusable IP to help us move faster, dive deeper, and work more efficiently by generalizing the algorithms, methodologies, and supporting infrastructure that you build. As one of the early hires to join the Noodle.ai team, you will have a significant impact on the future of Enterprise Artificial Intelligence.Job responsibilities:
- Implement a breadth of different modeling approaches/ techniques in machine learning
- Manipulate and prepare large, heterogeneous data sets to support advanced analytics
- Iteratively conceptualize, design and build data-driven analytical models
- Develop processes and tools to monitor and analyze model performance and data accuracy
- Translate deep mathematical concepts and practices into language that non-experts can understand and build upon. And conversely, translate business needs and user needs into language and concepts that other data scientists can understand and work with.
- Productionalizing machine learning code and interfacing with industry standardmsoftware systems
- Understand and manipulate unstructured data from different platforms.
- Demonstrate proficiency at real-world modeling problems/DS problems - getting to a result that demonstrably generate business value
Graduate degree in a relevant field (Computer Science, Operations Research, Statistics, Applied Math...) or Bachelors degree and 2-4 years applying advanced AI techniques to real-world problemsGood to have:
Skills and Competencies:
- 4 years of experience applying advanced AI techniques to real-world problems
- Experience tackling data science problems characterized as high-dimension, low sample size (i.e., lots of potentially predictive features and highly diverse but low quality or highly sparse data.)
- Knowledge & understanding of a functional area of focus (i.e. Experience applying advanced analytics to supply chain optimization, demand forecasting, and/or revenue management)
- Knowledge & understanding of an industry area of focus (i.e. retail, manufacturing,CPG, 3PL, travel...)
- Experience with common analysis tools (SQL, R, and Python).
- Demonstrable familiarity with code and programming concepts.
- Knowledge of Spark and/or Hadoop
- Knowledge of machine learning areas and techniques - Supervised machine learning,Unsupervised machine learning, Time series, Natural language processing, Outlier detection, Computer vision, Recommendation engines, Survival analysis,
Reinforcement learning, and Adversarial learning
- Knowledge of data visualization tools - ggplot, d3.js and Matplottlib, and Tableau
- Strong problem solving skills with an emphasis on product development
- Focus on delivering value and building lasting relationships through collaboration in an open and respectful working style
- Passion for learning and a desire to grow