Team8 Published: November 27, 2019
Job Type
Category
Level of education
Masters
Level of Hebrew
Medium
Location of job
Tel Aviv/ Ramat Gan
How many relevant years experience do you require for the role:
More than 3 years

Description

Noogata is an early stage startup with a mission to help large enterprises evaluate, build and roll-out machine-learning based applications. We are well funded (part of the Team8 startup foundry) and while we’re just getting started, we’re already engaged with some of the worlds largest organizations in retail, financial and media on their machine-learning initiatives.

We’re looking for brilliant, creative, ambitious, fun-loving engineers and data-scientist. If you’re all that and looking to lead, invent and grow professionally you should definitely consider applying to join us on our journey!

We are looking for experienced, savvy, data scientists to lead and execute machine learning projects in a wide range of industries (retail, banking, media, manufacturing) and domains (demand forecasting, NBO, content classification, …)

Responsibilities:
- Work with clients in a consultancy fashion to size business problems and how a data-driven scientific approach can be used to address them
- Coach and guide our team on best practices and approaches for building scalable, lasting data-science solutions
- Model training, tuning and performance evaluation using the latest tools and methods
- Evaluate technologies, define data pipeline and processing architectures to allow us to scale machine learning initiatives across our client base.

Requirements

- At least 5 years 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).
- Broad knowledge of data science modeling techniques (from RandomForests to RNNs and anything in between) and their use within the industry
- Hands-on experience with data science packages (TensorFlow, scikit, pyTorch) and tooling (Jupyter notebooks, Anaconda, Vega, ..)
- Experience in large scale training and model evaluation at an enterprise environment.
- Big Advantage: Experience with Cloud Machine Learning Platforms (Google ML Engine, AWS SageMaker) and/or commercial tools (DataRobot, BigML or others)
Customer facing.
- Willingness to travel.
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