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Senior Data Scientist

Pay
Pay not listed
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Build production forecasting and classification models such as demand forecasts and lead scoring

  • Build GenAI products using RAG, vector search, and agents with tool use

  • Run LLM API batch or async jobs with thousands of calls for labeling and extraction

  • Explain and debug models for non-technical stakeholders using SHAP

From the employer’s posting
Real forecasting and classification work (demand forecasts, lead scoring, propensity) in production or serious projects.
Has built (not only advised on) GenAI products: RAG, vector search, agents with tool use.
LLM APIs at scale: batch or async jobs with thousands of calls (data labeling, metadata extraction from text), not one-off prompts.
SHAP to explain and debug models for non-technical stakeholders.

What you’ll bring

All qualifications

Core experience

  • Strong SQL: complex joins, CTEs, window functions, query performance tuning
  • Strong Python and PySpark or similar
  • XGBoost and/or LightGBM used in production
  • Hands-on agentic coding with Claude Code, Codex, or Cursor
  • Azure and/or Databricks experience; GCP/Vertex or AWS/SageMaker acceptable
Qualification wording
Strong SQL: complex joins, CTEs, window functions, and query performance tuning.
Strong Python.
XGBoost and/or LightGBM in production.
Hands-on agentic coding with Claude Code, Codex, or Cursor.
Azure and/or Databricks (both preferred).

Tools in this posting

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • GCP
  • SageMaker
  • LightGBM
  • PySpark
  • XGBoost
Source — Tool mentions in context
- Strong SQL: complex joins, CTEs, window functions, and query performance tuning. - Strong Python. - PySpark or similar.
Must-have: Core ML - Strong SQL: complex joins, CTEs, window functions, and query performance tuning. - Strong Python.
- Azure and/or Databricks (both preferred). - Strong GCP/Vertex or AWS/SageMaker experience is acceptable. #LI-DC10
Must-have: Platform - Azure and/or Databricks (both preferred). - Strong GCP/Vertex or AWS/SageMaker experience is acceptable.
- Real forecasting and classification work (demand forecasts, lead scoring, propensity) in production or serious projects. Coursework does not count. - XGBoost and/or LightGBM in production. - SHAP to explain and debug models for non-technical stakeholders.
- Strong Python. - PySpark or similar. - Real forecasting and classification work (demand forecasts, lead scoring, propensity) in production or serious projects. Coursework does not count.

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 5, 20262 days ago
Recorded sightings
1

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 2

Early. Similar jobs usually come down between day 7 and day 57.

From 10,553 similar postings that came down. Coming down is not always a hire.

Capgemini Service SAS is hiring

293 open jobs

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

Hiring record

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About Capgemini Service SAS

People
About 11,267 in 2024.Benefit plan filings (Form 5500)
Company
Listed as CAP.PA.
H-1B visas
771 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,815.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 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 ↗

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

Job Description

Your Role:

Must-have: Core ML

  • Strong SQL: complex joins, CTEs, window functions, and query performance tuning.
  • Strong Python.
  • PySpark or similar.
  • Real forecasting and classification work (demand forecasts, lead scoring, propensity) in production or serious projects. Coursework does not count.
  • XGBoost and/or LightGBM in production.
  • SHAP to explain and debug models for non-technical stakeholders.

 

Must-have: GenAI / Agentic

  • Hands-on agentic coding with Claude Code, Codex, or Cursor.
  • Has built (not only advised on) GenAI products: RAG, vector search, agents with tool use.
  • LLM APIs at scale: batch or async jobs with thousands of calls (data labeling, metadata extraction from text), not one-off prompts.

 

Must-have: Platform

  • Azure and/or Databricks (both preferred).
  • Strong GCP/Vertex or AWS/SageMaker experience is acceptable. 

 

#LI-DC10

 

#LI-Remote

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

Source details

View original posting ↗

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Pay

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Location & working pattern

Bogota, CO

#LI-DC10 #LI-Remote Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
Work authorization

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