Time since we first saw it
Day 2
Early. Similar jobs usually come down between day 7 and day 57.
From 10,509 similar postings that came down. Coming down is not always a hire.
Senior Data Scientist
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingBuild 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 qualificationsCore 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
Report an errorActively 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
Capgemini Service SAS is hiring
346 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordYour next step
Check the employer’s posting for the current role and application details.
Applying through SAP SuccessFactors
- Images (.jpg) aren’t accepted as a resume.
Already applied? Track this application
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.
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
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
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- 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
No clear work-authorization passage found. Eligibility is unconfirmed.
AI answers unavailable
We couldn’t identify enough role detail in this saved description to support an AI answer. Read the full posting