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Senior Data Scientist
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Work setup in the employer’s posting: TELECOMMUTE
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingDevelop forecasting solutions for Accounts Receivable and/or Accounts Payable
Build regression and time-series models using Python and SageMaker
Cleanse and refactor complex data from multiple sources for modeling
Create data visualizations that explain insights to non-technical audiences
From the employer’s posting
Develop data science solutions for forecasting Accounts Receivable and/or Account Payable
Work with SageMaker to leverage its capabilities for model development
Cleanse, filter, and refactor complex data from different sources
Create data visualizations to communicate insights to non-technical audiences
What you’ll bring
All qualificationsCore experience
- 5+ years developing and delivering data science solutions
- Expertise in Python for data analysis and modeling
- Strong knowledge of regression and time-series problem-solving
- Experience in statistical analysis with Python
- English at Upper-Intermediate (B2) level or higher
Qualification wording
5+ years of experience in developing and delivering data science solutions
Expertise in Python for data analysis and modeling
Strong knowledge of regression and time-series problem-solving using advanced analytics methodologies
Experience in statistical analysis and programming with Python
English language proficiency at an Upper-Intermediate level (B2) or higher
Tools in this posting
- Python
- SQL
- Azure
- Redshift
- S3
- SageMaker
- SAP
- Tableau
Source — Tool mentions in context
Our client is one of the world’s leading agriculture companies. Their mission is to contribute to the secure feeding of the world while prioritizing environmental responsibility. Their objective is to enhance the sustainability, quality, and safety of agriculture through cutting-edge scientific expertise and inventive crop solutions. The technologies our client employs empower millions of farmers worldwide to optimize the utilization of scarce agricultural resources. Responsibilities Develop data science solutions for forecasting Accounts Receivable and/or Account Payable, with a strong emphasis on accuracy and integrity Work with SageMaker to leverage its capabilities for model development Solve regression and time-series-related problem statements using various advanced analytics methodologies, including Linear Regression, Machine Learning, Deep Learning, clustering, classification, segmentation, and more Perform model development and validation to improve model accuracy Cleanse, filter, and refactor complex data from different sources, and analyze it to identify its potential for generating high-accuracy models Utilize Python for data analysis and modeling Apply different machine learning algorithms to solve complex business problems Conduct statistical analyses and advanced data management using Python Create data visualizations to communicate insights to non-technical audiences Requirements 5+ years of experience in developing and delivering data science solutions Experience in forecasting Account Receivable and/or Account Payable is highly beneficial Strong knowledge of regression and time-series problem-solving using advanced analytics methodologies Expertise in Python for data analysis and modeling Experience in statistical analysis and programming with Python Ability to create data visualizations for non-technical audiences English language proficiency at an Upper-Intermediate level (B2) or higher Nice to have Experience with data science use cases within business finance, production, supply, or commercial space Ability to explain complex data and analysis in a concise and understandable manner Familiarity with corporate financial data Understanding of SAP ECCs Experience with common analytics technologies such as SAP Analytics Cloud, Qlik, Tableau, Sage Maker, Azure ML, Data Bricks, KNIME, Alteryx, SAP BW, Redshift, S3, SQL, and others Proficiency in Sage Maker
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 1, 20262 days ago
- Recorded sightings
- 4
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Sep 29, 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
EPAM Systems is hiring
656 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordYour next step
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Has EPAM Systems posted this job before?
Yes. We’ve followed 19 other Senior Data Scientist jobs there since November 2026. All 19 are still up.
Large employers often post one title for several teams, so these can be separate openings.
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
Our client is one of the world’s leading agriculture companies. Their mission is to contribute to the secure feeding of the world while prioritizing environmental responsibility. Their objective is to enhance the sustainability, quality, and safety of agriculture through cutting-edge scientific expertise and inventive crop solutions. The technologies our client employs empower millions of farmers worldwide to optimize the utilization of scarce agricultural resources. Responsibilities Develop data science solutions for forecasting Accounts Receivable and/or Account Payable, with a strong emphasis on accuracy and integrity Work with SageMaker to leverage its capabilities for model development Solve regression and time-series-related problem statements using various advanced analytics methodologies, including Linear Regression, Machine Learning, Deep Learning, clustering, classification, segmentation, and more Perform model development and validation to improve model accuracy Cleanse, filter, and refactor complex data from different sources, and analyze it to identify its potential for generating high-accuracy models Utilize Python for data analysis and modeling Apply different machine learning algorithms to solve complex business problems Conduct statistical analyses and advanced data management using Python Create data visualizations to communicate insights to non-technical audiences Requirements 5+ years of experience in developing and delivering data science solutions Experience in forecasting Account Receivable and/or Account Payable is highly beneficial Strong knowledge of regression and time-series problem-solving using advanced analytics methodologies Expertise in Python for data analysis and modeling Experience in statistical analysis and programming with Python Ability to create data visualizations for non-technical audiences English language proficiency at an Upper-Intermediate level (B2) or higher Nice to have Experience with data science use cases within business finance, production, supply, or commercial space Ability to explain complex data and analysis in a concise and understandable manner Familiarity with corporate financial data Understanding of SAP ECCs Experience with common analytics technologies such as SAP Analytics Cloud, Qlik, Tableau, Sage Maker, Azure ML, Data Bricks, KNIME, Alteryx, SAP BW, Redshift, S3, SQL, and others Proficiency in Sage Maker
Source details
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