About Zone7

Zone7 is a cloud-based platform delivering AI algorithms that analyze athlete data to reduce the risk of injury and improve athlete performance. By analyzing data from thousands of athletes, we find complete patterns that lead to injury or peak performance and apply these learnings to create optimal recovery and workload plans. We work with soccer, hockey, and baseball teams in the US, Spain, UK, Italy, China, and more. Clients report a reduction in injuries and absences of 65%. We've also partnered with early adopters in healthcare – monitoring ER staff for exhaustion and Special Forces.

The company is based in SV and Tel Aviv and is backed by VC firms Resolute Ventures and UpWest as well as athletes such as Kristaps Porzingis, Jordi Cruyff, and Phil Jones.

Job Description

Position Overview

We’re looking for an experienced Data Scientist that can bring a substantial added value to our data science team. This position will include analysis of match stats, performance data, physiological tracking, biomechanical screening, and health biomarkers, to upgrade existing algorithms and develop new algorithms, alongside the delivery of algorithm outputs to a non-tech environment. This position will also enable you to take a key role in further building the company, alongside having a decisive influence on our product, data science stack, and infrastructure. 

What You’ll Do

• Build our ML & DL models and recommendations engine.
• Bring in new methods to upgrade our platform's performance and quality of insights.
• Develop the infrastructure we use to import and integrate the different data types we analyze.
• Design and implement data science stack upgrades that will enable scaling the solutions we currently offer.
• Tailor our solutions for elite organizations’ specific requirements

Skills and Requirements

What You Need

• Be able to successfully work in a team and communicate opinions and insights to help develop the company.
• Significant experience in problem-solving using ML and DL methods.
• Experience with Cloud Big Data computing design, provisioning, and tuning.
• Experience with Big Data technologies (e.g., Spark, Hadoop, NoSQL engines, different data file formats).
• Knowledge of scripting and programming languages such as Python is mandatory.
• Experience with data from sensors and time series data is an advantage.
• Passion for sports is an advantage. A background in competitive sports even more so.
• Knowledge in life science, especially exercise physiology or biomechanics is an advantage as well.

Outbrain is a leader in recommendation technologies for the open web. We recommend millions of articles and ads per second and we’re always on the lookout for passionate and innovative individuals who are looking to help drive the best discovery experience on the web.

Our team is developing machine learning algorithmic solutions that improve outcomes for our advertisers. It is part of Outbrain’s Recommendations Group – about 40 machine learners, data scientists and backend engineers who are responsible for everything that Outbrain recommends in its feeds and widgets. The team uses an interplay of Python, Java and Rust, in addition to Spark, Bigquery, and Tensorflow to form our ML and AutoML pipelines.

Your team’s responsibilities are: 

• Understanding business goals of advertisers and exploring solutions to achieve them
• Algorithm research, development, evaluation, optimization for CPA and ROAS
• A/B testing and model deployment using fast development and deployment cycles
• Improvements of our ML pipeline and AutoML capabilities

Your personal responsibilities are:

• Identifying and deciding on promising research and development directions, balancing short term and long term goals
• Mentoring data-scientists and helping with their professional development
• Communication and coordination with product and business counterparts

Who you are:

• You have machine learning industry experience from AdTech, MarTech or online marketplaces
• BScMScPhD in Computer Science, Statistics, Software, Information Systems Engineering or similar or equivalent industry experience
• Deep understanding of statistics (e.g., hypothesis testing, regressions, ML systems)
• Experience with deploying ML algorithms in an online production environment
• Experience in SQL.
• Experience in a scripting language (Python preferred).
• Great communication and interpersonal skills
• Experience in Recommender System, Conversion Optimization or AutoML – an advantage
• Experience with one or more deep learning frameworks – an advantage

What we offer:

• Competitive salary and great work/life balance.
• Working fully remotely due to COVID in the foreseeable future.
• Making a business and technical impact in a global company. The company is global, but at the same time small enough that a single person in this position can have a significant impact.
• Stay on top of applicative research in the field, visit conferences (online and on-site when they are back) and publish research

SuperSmart is looking for a deep learning engineer with experience in computer vision.

Requirements:

• Python + PyTorch/Keras/Tensorflow
• Work portfolio/Git/Kaggle
• Practical experience with object detection/object recognition

Bonuses:

• Sense of humor
• Experience of work in start-up environment
• Experience in classical Computer Vision and Machine Learning

About us:

SuperSmart is a self-checkout services provider in the field of retail. In Israel it is represented in the Osher Ad supermarkets.

Offices are located in Rosh Haayin. Partially remote work option is available.

Good balance between work and personal life. Family atmosphere.

The problem we are trying to solve is not trivial and challenging. If you like challenges, we are looking forward to seeing you in our squad.

Maverick Medical AI is an early commercial-stage company with a footprint in Israel and the US and offers the first commercially trained neural network based on big data of real sub-specialized clinical data

Our Clinical AI Cognition™ Platform interprets and understand unstructured clinical text just like a physician would. We can surface contextual clinical insights and indications that are often hidden across multiple areas of the patient's documentation and convert them into evidence-based diagnostic codes. Capturing every possible diagnosis at its highest specificity level drives revenue opportunities.

We are looking for a hands-on algorithm developer to join our core R&D team. We search for candidates who are experienced with modern NLP methods, deep learning and python and ready to face Big Data challenges. You will be working on real world problems, develop cutting edge NLP technology, and have a massive impact on our product.

Outbrain's yield optimization team is looking for an experienced Algorithms Engineer. The team is part of Outbrain’s Recommendations Group – about 40 machine learning engineers, data scientists and backend engineers who are responsible for everything that Outbrain recommends in its feeds and widgets. The team is involved in research, implementation and production rollout of state of the art machine learning models in diverse tech stack Python, TensorFlow, Java and Rust.

Yield Optimization teams responsibilities: 

We are developing state-of-the-art CTR prediction models which are the backbone of Outbrain recommender systems. We leverage Outbrain AutoML suite to accelerate our research and to reduce productization time. We do extensive feature research, develop state of the art models in TensorFlow and Rust. In addition we tackle classical recommender system challenges such as cold start.

For more info go to job submission page i the link bellow

This is Artlist 🎵

Artlist is a fast-growing music licensing platform for filmmakers. With tens of thousands of customers and outstanding growth, Artlist is helping filmmakers around the world achieve their creative freedom.

The Opportunity 🎸

We're looking for a passionate Machine Learning Engineer to take part in designing and building our AI/ML Platform. 

If you you’re passionate about AI/ML, have a strong software engineering background with Python and experienced with bringing code to a production grade -> You’re at the right place

You’ll be a part of a new Data science team of researchers and engineers and will lead the engineering efforts in terms of tools and standards.

Responsibilities:

• Build infrastructure for running inference and training on various data types – video, music, tabular
• Design and build scalable data processing pipelines
• Optimize models speed and memory consumption
• Dockerize workloads 
• Build tools for visualizations

In this role, you'll work closely with our Data Science and Backend Engineering teams to build our entire ML platform, from model training to production. This is a valuable opportunity to take a significant role in scaling algorithms on a popular global platform.

Requirements

• 4+ years experience in software engineering
• BSc in Computer Science, Mathematics, or any related degree
• All-around team player who is a self-motivated, fast learner
• Strong programming skills in Python
• Background working with a cloud technology stack like AWS, Azure, or GCP
• Experience working on high-scale, production-grade projects
• Knowledge of relational and NoSQL databases
• Experience with training, testing, deployment, and monitoring real-time (or near real-time) machine learning models in production is a plus

This is Artlist 🧑‍🎨

Artlist is a fast-growing music licensing platform for filmmakers. With tens of thousands of customers and outstanding growth, Artlist is helping filmmakers around the world achieve their creative freedom.

The Opportunity ♫

We are looking for an experienced Data scientist to join our data science team.

As a data scientist you’ll define, research, develop and deploy models – impacting artists and creators all over the world!

Working with us means training your model on diverse data created by the top filmmaker and musicians worldwide (you’ll love it!)

What you’ll do:

• Build cutting edge models and data pipelines to develop valuable features for our users like
  • Recommendation systems empowering creators all over the world
  • Optimizing user journeys on our platform
  • Analyzing top quality labelled data
• Write production grade code, served to our user audience
• Understand the business and product needs and transform them into successful scientific and production ready solutions
• Experiment with state of the art algorithms and tools on various data types (tabular, audio, video)

Requirements:

• Minimum of 3 years of hand-on data science 
• Extensive knowledge of ML disciplines and algorithms, with a focus on tabular methods (deep and classical ML)
• Excellent programming skills in python, knowledge in SQL
• Experience with recommendation systems – Big Plus
• Software engineering background – Plus
• Passionate about music & art – Plus

Computer Vision Researcher

Responsibilities:

Research and implement state-of-the-art computer vision algorithms.

Qualifications:

• M.Sc./Ph.d in computer science/electrical engineering/physics/ mathematics.
• At least 3-year experience in research and development of computer vision algorithms.
• Strong mathematical skills.
• Deep understanding of multi-view geometry and stereo imaging.
• Proficient in c++.

Advantages:

Knowledge of SLAM algorithms.

Knowledge of estimation theory, sensor fusion, Kalman filters.

Knowledge of large scale optimization methods (e.g. bundle adjustment).

ClimaCell’s Product & Engineering department is focused on building changing lives software and products at scale, from infrastructure that handles massive amounts of data to outstanding customer-centric user experiences in B2B, B2C and B2D products that change billions of lives worldwide.

We’re looking for a Product Data Scientist, that will support the growth by creating dashboards, interpreting data, sharing insights, and developing models that improve every aspect of the product. You'll Build the data methodologies and processes and enable all the different product teams to take better and smarter data-driven decisions.You’ll help ClimaCell consumer app grow to hundreds of millions of users by gathering and extracting business insights.

As a Product Data Scientist at ClimaCell, You’ll be the “data eyes and ears” that guide the product team. You’ll find what’s working, what can be improved and what’s missing. On a daily basis, you will work with the key stakeholders in the company, make decisions, and get the chance to make an impact.
And…You'll help us make sure we are building the biggest weather platform in the world!

What you bring:
5+ years proven experience using SQL, Python/R.
5+ years experience doing quantitative analysis, in web or mobile company.
5+ Experience with online product analysis: funnel optimization, flows, cohorts, feature impact, retention and more.
Experience in developing visualization tools (Tableau, Looker, etc.).
Very Strong experience in writing complex SQL queries.
Strong knowledge of working with large and complex datasets that represent the whole user lifecycle (user behavior, purchases, marketing, etc.)
Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to details and accuracy.
Autodidact, Independent, self-motivated and able to produce accurate and reliable results.
Ability to leading data-driven projects from definition to execution.
Ability to thrive in an unstructured environment, working autonomously with a strong team to find opportunity and deliver business impact.
Advantage:
data engineering skills.

So if Data is your middle name, you're a creative thinker and your friends call you when they need your insights, and if you love the rain – this is the team for you.

About Us

Riskified is the AI platform powering the eCommerce revolution. We use cutting-edge technology, machine-learning algorithms, and behavioral analytics to identify legitimate customers and keep them moving toward checkout. Merchants use Riskified to increase revenue, prevent fraud, and eliminate customer friction. Riskified has reviewed hundreds of millions of transactions and approved billions of dollars of revenue for merchants across virtually all industries, including Wish, Prada, Aldo, Finish Line, and many more. We're privately funded and VC backed, and our recent Series E round raised $165 million with a valuation in excess of $1 billion. Check out the Riskified Technology Blog for a deeper dive into our R&D work.

About the Role

The Research department is at the core of Riskified’s solution, responsible for our chargeback guarantee product and focused on bringing value to Riskified through the development of algorithms and analytical solutions. The department uses a wide variety of advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more).

The ML Algorithm team is responsible for the full life-cycle of model development in Riskified. This includes defining, researching and implementing our traditional machine learning process in a fully automated fashion to enable fast and effortless model training and deployment. Additionally, the team is focused on automating increasingly complex aspects of the model configuration – dynamically setting thresholds to respond to population changes and segmenting the population in a smart fashion to improve the accuracy of each model. To enable this, we harness the latest MLOps architectures and require solid statistical foundations to ensure the quality of our products. 

Our vision is to automate much of our internal data science and analytics work through advanced algorithm and machine learning engineering, pushing Riskified’s world-class solutions to the next stage.

We are looking for a full-stack Data Scientist / ML Engineer, with a strong background both in statistical modelling and writing production code. Experience with MLOps methodologies is a big advantage.

What You'll Be Doing

• Design, optimize and automate the full life-cycle of models in Riskified – Training, Deployment, Monitoring 
• Collaborate with various teams within Riskified to enhance processes and expedite model development life-cycles
• Design algorithms to optimize models’ configurations for multiple merchants and under several various constraints including dynamic population changes
• Optimize, automate and monitor the whole model training and deployment process

Qualifications

• At least 2 years of experience as a Data Scientist/ML engineer in the industry
• M.Sc/Ph.D. in exact sciences/engineering disciplines
• Ability to write clean and concise code, ideally in R or Python
• Experienced with data science best-practices
• Solid understanding of statistics and applied mathematics
• Creative thinker with a proven ability to innovate through data exploration and application of advanced solutions
• Dedication and persistence when it comes to monitoring and improving performance after deployment
• Good communication skills, ability to clearly explain complex concepts
• Experience writing production code – Advantage
• Experience using Spark/Docker/Kubernetes and CI/CD – Advantage
• Experience with Bayesian Optimization / Control systems – Advantage

Life at Riskified

We are a fast-growing and dynamic startup with 500+ team members between our offices in Tel Aviv, New York City, and Shanghai. We value collaboration and innovative thinking. We’re looking for bright, driven, and passionate people to grow with us.

Some Tel Aviv Benefits & Perks:

• Stock options for all employees
• Keren Hishtalmut and pension
• Extra time off for parents and caregivers
• Commuter and parking benefits
• Team events, fully-stocked kitchen, lunch stipend, yoga, pilates, basketball, soccer, and more