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Customer-Facing Data Scientist – Demand Forecasting

Ramat Gan, Tel Aviv District, Israel

Actively hiring, first seen by us 3 days ago
Pay
Pay not listed
Work setting
Not stated
Employment
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What you’ll work on

Full posting
  • Test the core ML pipeline on new customer data and fix cases where it underperforms

  • Dive into clients' datasets to understand their business challenges

  • Optimize and deploy demand forecasting models in production

  • Apply time series techniques such as ensembling, anomaly detection, and causal inference

From the employer’s posting
Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not.
diving deep into their unique datasets to understand the nuances and challenges of their business
focusing on the optimization and deployment of Demand Forecasting models.
forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling.

What you’ll bring

All qualifications

Core experience

  • 5+ years of experience as a data scientist working on tabular and time-series data
  • Experience working with Customers (in English) – an advantage
  • Proficient in Python, SQL, and Spark
  • Proven experience in creating measurable value with ML (defining KPIs, designing A/B tests, monitoring models in production)
  • Deep experience with time series modeling and forecasting techniques
  • Experience with AWS / Databricks – an advantage
Qualification wording
5+ years of experience as a data scientist working on tabular and time-series data
Experience working with Customers (in English) – an advantage
Proficient in Python, SQL, and Spark
Proven experience in creating measurable value with ML (defining KPIs, designing A/B tests, monitoring models in production)
Deep experience with time series modeling and forecasting techniques
Experience with AWS / Databricks – an advantage
Apply at Pecan AI

Posting record

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Actively hiringFirst seen by us 3 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 10, 20263 days ago
Recorded sightings
4
Last seen by us
Nov 13, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 3

Early. Similar jobs usually come down between day 8 and day 60.

From 11,783 similar postings that came down. Coming down is not always a hire.

Pecan AI is hiring

3 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Databricks
  • SageMaker
  • Snowflake
  • Spark
Where the posting names them
- BSc in a relevant field (e.g., Computer Science, Engineering, Statistics) - Proficient in Python, SQL, and Spark - Proven experience in creating measurable value with ML (defining KPIs, designing A/B tests, monitoring models in production)
- Deep experience with time series modeling and forecasting techniques - Experience with AWS / Databricks – an advantage - MSc/Research experience – an advantage
Compare Pecan vs. Amazon SageMaker and Databricks Pecan vs Google Vertex AI and Snowflake Pecan vs Akkio vs Peak AI Pecan vs Alteryx vs Qlik Predict Pecan vs DataRobot vs Dataiku Product

Your next step

Complete your application on www.pecan.ai. The employer’s form will show what is required.

Already applied? Track this application

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 1,403, the most 2,949, and the latest week had 2,098.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

DS
Customer-Facing Data Scientist – Demand Forecasting

Pecan is an automated, AI-based predictive analytics platform that simplifies and accelerates the process of building and deploying machine learning models across various business use cases. Learn more about our dedicated offering here: demandforecast.ai.
Pecan connects to the raw data and completely automates the data preparation, engineering, and preprocessing phases, as well as the model training and evaluation lifecycle. It was acknowledged as one of Israel’s 50 most promising startups for two consecutive years.


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.
  • +50 employees
  • HQ in Tel Aviv with a 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, Mars, and SciPlay.

Demand Forecasting Team

The Demand Forecasting team is at a pivotal, high-growth stage. We have successfully built our core pipeline and are now aggressively onboarding new, diverse customers. This role is highly dynamic, requiring a blend of technical depth, proactive research, and exceptional communication to adapt our platform to real-world customer data and challenges. You will be a critical link between the core product and our clients’ business success.

Responsibilities

As a key Customer-Facing Data Scientist on the Demand Forecasting team, you will:

  • Work at the forefront of the data world, focusing on the optimization and deployment of Demand Forecasting models.
  • Handle complex data science challenges using state-of-the-art techniques relevant to demand forecasting and time series, such as forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling.
  • Act as a highly communicative partner to our clients, diving deep into their unique datasets to understand the nuances and challenges of their business.
  • Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not.
  • Be instrumental in helping our clients achieve their business goals and realize the measurable value of Pecan’s Demand Forecasting module.
  • Work within a production and product-oriented environment, ensuring models are robust, scalable, and directly integrated into the client’s operational workflow.

What We Are Looking For

  • 5+ years of experience as a data scientist working on tabular and time-series data
  • BSc in a relevant field (e.g., Computer Science, Engineering, Statistics)
  • Proficient in Python, SQL, and Spark
  • Proven experience in creating measurable value with ML (defining KPIs, designing A/B tests, monitoring models in production)
  • Deep experience with time series modeling and forecasting techniques
  • Experience with AWS / Databricks – an advantage
  • MSc/Research experience – an advantage
  • Experience working with Customers (in English) – an advantage
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