This role pays less than
96%
of similar roles. Most pay
$126,800–$196,387
— the shaded band above.
At the midpoint, this role pays about
$104k
versus about
$162k
for comparable roles.
Based on 240 similar postings.
Employer
About P&G
Procter & Gamble (P&G) is one of the world''s largest consumer goods companies, marketing a broad portfolio of household and personal care brands including Tide, Pampers, Gillette, and Crest. Industry: Consumer Goods
P&G currently has
5 open roles
on FindRole.
Listed pay typically runs
$85,000–$122,200
across 5 roles with salary data.
As a Data Scientist, you will join a team focused on solving complex problems by turning untidy data into nonobvious insights through advanced Artificial Intelligence. You will research, design, and customize algorithms tailored to various data types while collaborating with Data and Software Engineering teams to productionize solutions in cloud environments. Your daily work involves exploratory data analysis, feature engineering, and model building using techniques such as tree models, deep learning, reinforcement learning, optimization, and simulation. The role specifically integrates Generative and Agentic AI to create dynamic models for large datasets. You will utilize Python along with libraries like OpenCV, scikit-learn, PyTorch, TensorFlow/Keras, and Pandas. Additionally, you will serve as a technical coach, mentoring others while becoming an expert in specific data science methodologies to improve business outcomes through scalable algorithmic development.
What does a Data Scientist earn?
Median $162025 from 276 postings across 61 companies.
Design and develop scalable data science algorithms using machine learning, optimization, and simulation techniques.
Integrate Generative and Agentic AI technologies to create dynamic and responsive models.
Perform exploratory data analysis and feature engineering on massive datasets within cloud environments.
Partner with Data and Software Engineering teams to productionize models and solutions.
Research and customize algorithms tailored to specific business problems and diverse data types.
Act as a technical coach to mentor others and share expertise in data science methodologies.
Quantify the measurable improvements in business outcomes resulting from implemented models.
What we're looking for
Pursue or hold a Master’s degree in a quantitative field such as Operations Research, Computer Science, Engineering, Applied Mathematics, Statistics, Physics, or Analytics.
Possess equivalent work experience in lieu of a Master's degree.
Proficiency in programming languages like Python and libraries including OpenCV, scikit-learn, PyTorch, TensorFlow/Keras, and Pandas.
Demonstrated ability to develop and test code within cloud environments such as GCP or Azure.
Experience applying machine learning, optimization, simulation, and Generative and Agentic AI to real-world problems.
Familiarity with DevOps environments, including tools like Git and CI/CD practices.
Strong written and verbal communication skills with the ability to influence others.
Stennis Space Center, MS48 days ago
$99,000–$225,000
Python
R
SQL
SAS
MATLAB
Machine Learning
Artificial Intelligence
Natural Language Processing
Spark
Databricks
ElasticSearch
NiFi
Palantir Foundry
Tableau
Power BI
Qlik
Plotly
Seaborn
ggplot2
Big Data