Data Analyst (Client-Facing)

an automated AI-based predictive analytics platform. It simplifies and accelerates the process of building and deploying predictive models in various business use-cases, such as life-time value, Churn, demand forecast and more. connects to the raw data and completely automates the data preparation, engineering and prepossessing phases, as well as the model training and evaluation lifecycle. It was acknowledged as one of Israel's 50 most promising startups two years in a row.

Company Highlights:
Series C company with over $117M raised to date. Tier-1 investors: Google Ventures (GV), Insight Partners, GGV, Dell Ventures, Mindset and S Capital.
90+ employees and growing very quickly
HQ in Tel Aviv with growing sales and marketing organization in the US
Customers across CPG, retail, healthcare, mobile apps, fintech, insurance, and consumer services. Marquee customers include Johnson & Johnson, Nestle, and SciPlay.
The Data Analyst is a part of the Customer Success team, which is responsible for all of our clients, starting from the POC stage and through deployment in production environments. The CS team assists our clients in the design, planning, and implementation of predictive analytics programs. We are looking for an enthusiastic and client-focused data analyst.

What You'll Do

As a data analyst, you will work at the forefront of the data world, by creating and optimizing predictive models and assisting our clients to use those predictions to affect their business and generate value.

Together with the team, you will be continuously helping our clients achieve their business goals and reinforce the value. You'll assist in covering data and technical aspects of integrating clients systems with our predictive analytics platform.

Typical tasks of the position are:

Collaborate with the clients business stakeholders, gather technical requirements, and understand the need for predictive models.
Analyze large volume of data sets using different coding languages as SQL and Python.
Analyze the models outputs and explain complex concepts in simple words.
Collaborate with clients teams and translate business needs to data solutions.
Be the data and technical point of contact for our clients, and understand their needs.
Develop tools and data research to improve the quality of predictions.