Noogata-Data Scientist

About The Position

Noogata is the leader in no-code artificial intelligence (AI) designed from the ground up for citizen data analysts. We’re democratising AI for enterprises and making it accessible to the common business user. Founded in 2019, backed by world-class VCs and offices in Tel Aviv and NYC, Noogata is one of the fastest-growing and most exciting companies in the Enterprise AI space. 

We are looking for experienced, savvy, data scientists to lead and execute machine learning projects across multiple domains (demand forecasting, NBO, content classification, …) and throughout their lifecycle – from early feasibility research to productization and ownership of models. 

Responsibilities

• Be part of a data-science team where you will lead end-to-end ML projects. (from data extraction through model validation & A/B testing to model deploying)
• Develop supervised and unsupervised machine learning models as part of the Noogata no-code AI Enterprise offering
• Develop and manage continuous-training pipelines to deliver models to production. Own and operate the process, continuously improving model performance
• Work with engineering team to develop data collection strategies to create more value and accuracy in models 
• Be part of a startup company: Help setting priorities and making design decisions based on your experience and insights.

Requirements:

• MSc or equivalent experience in a quantitative field (Statistics, Mathematics, Engineering, Economics, etc.)
• At least 5 years experience Hands-on experience with data science projects from early-stage concept to production rollouts
• Experience in managing data science projects/programs/teams.
• Broad expertise in multiple industries/domains (vs a single field specialist).
• An all-around data scientist: strong statistics background, strong analytical mindset, experience in experimentation, data visualization, machine learning algorithms, optimization and big data.
• Broad knowledge of data science modeling techniques (ML, GLM, Clustering, DL, etc.) and their use within the industry SageMaker)
• Experience with Python and SQL.
• Excellent communication & interpersonal skills

Big Advantage: 

• Experience with Cloud Platforms (GCP, AWS)
• Experience in working in an agile data science methodology