Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Data Science Engineer
Fremont, CA · On-site
$125K - $151K/yr
Responsibilities : • Develop and maintain ETL pipelines using AWS Glue for data ingestion, transformation, and integration from various sources. • Utilize Python and Spark for data preprocessing ...
Data Science Engineer
Fremont, CA · On-site
$125K - $151K/yr
Responsibilities : • Develop and maintain ETL pipelines using AWS Glue for data ingestion, transformation, and integration from various sources. • Utilize Python and Spark for data preprocessing ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions -- from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions -- from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions -- from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions -- from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions -- from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions -- from data preprocessing, feature engineering, experimentation, and validation through to deployment ...
IT - Technology Lead | Machine Learning | PYTHON
San Jose, CA · On-site
$164K - $202K/yr
Conduct data preprocessing, feature engineering, model evaluation, and performance tuning.Build robust, modular, and Minimum years of experience*: 8-10 years
IT - Technology Lead | Machine Learning | PYTHON
San Jose, CA · On-site
$164K - $202K/yr
Conduct data preprocessing, feature engineering, model evaluation, and performance tuning.Build robust, modular, and Minimum years of experience*: 8-10 years
Expertise in data preprocessing, feature engineering, and advanced model evaluation techniques (e.g., A/B testing, causal inference). Preferred: * Master's or PhD in a Science or Engineering field.
Expertise in data preprocessing, feature engineering, and advanced model evaluation techniques (e.g., A/B testing, causal inference). Preferred: * Master's or PhD in a Science or Engineering field.
Data Scientist
Pleasanton, CA · On-site
Experiencewith data preprocessing, feature engineering, and model evaluationtechniques. * Knowledgeof deep learning architectures (CNNs, RNNs, Transformers) and theirapplications. * Proficiencyin ...
Data Scientist
Pleasanton, CA · On-site
Experiencewith data preprocessing, feature engineering, and model evaluationtechniques. * Knowledgeof deep learning architectures (CNNs, RNNs, Transformers) and theirapplications. * Proficiencyin ...
Software Engineer, AI Training and Infrastructure
San Mateo, CA · On-site
$100K - $300K/yr
Develop and maintain robust, scalable, and distributed training pipelines (data preprocessing, training orchestration, and model evaluation) and frameworks for large-scale AI models. * Optimize ...
Software Engineer, AI Training and Infrastructure
San Mateo, CA · On-site
$100K - $300K/yr
Develop and maintain robust, scalable, and distributed training pipelines (data preprocessing, training orchestration, and model evaluation) and frameworks for large-scale AI models. * Optimize ...
Data Scientist
Pleasanton, CA · On-site
Experiencewith data preprocessing, feature engineering, and model evaluationtechniques. * Knowledgeof deep learning architectures (CNNs, RNNs, Transformers) and theirapplications. * Proficiencyin ...
Data Scientist
Pleasanton, CA · On-site
Experiencewith data preprocessing, feature engineering, and model evaluationtechniques. * Knowledgeof deep learning architectures (CNNs, RNNs, Transformers) and theirapplications. * Proficiencyin ...
Data Engineer
San Jose, CA · On-site
$134K - $161K/yr
... for data preprocessing, feature engineering, model training, validation, and deployment using tools like Vertex AI, BigQuery. etc. · Conduct deep data analysis to uncover insights, validate ...
Data Engineer
San Jose, CA · On-site
$134K - $161K/yr
... for data preprocessing, feature engineering, model training, validation, and deployment using tools like Vertex AI, BigQuery. etc. · Conduct deep data analysis to uncover insights, validate ...
Research Statistician (Part-Time)
Orange, CA · On-site
$40 - $50/hr
Key responsibilities include preprocessing data for analysis, performing complex data analysis, manuscript writing, publishing research findings in peer-reviewed journals, and mentoring junior ...
Research Statistician (Part-Time)
Orange, CA · On-site
$40 - $50/hr
Key responsibilities include preprocessing data for analysis, performing complex data analysis, manuscript writing, publishing research findings in peer-reviewed journals, and mentoring junior ...
Research Statistician (Part-Time)
Orange, CA · On-site
$40 - $50/hr
Key responsibilities include preprocessing data for analysis, performing complex data analysis, manuscript writing, publishing research findings in peer-reviewed journals, and mentoring junior ...
Research Statistician (Part-Time)
Orange, CA · On-site
$40 - $50/hr
Key responsibilities include preprocessing data for analysis, performing complex data analysis, manuscript writing, publishing research findings in peer-reviewed journals, and mentoring junior ...
Conduct end-to-end experiments, including data preprocessing, feature engineering, model training, validation, and deployment. Drive initiatives independently with high ownership and accountability.
Conduct end-to-end experiments, including data preprocessing, feature engineering, model training, validation, and deployment. Drive initiatives independently with high ownership and accountability.
The role involves data collection, preprocessing, quality assurance, and collaboration with cross-functional teams to enhance the machine learning pipeline and support geotypical production.
The role involves data collection, preprocessing, quality assurance, and collaboration with cross-functional teams to enhance the machine learning pipeline and support geotypical production.
Data Preprocessing information
What is data preprocessing?
Data preprocessing is the process of cleaning, transforming, and organizing raw data into a usable format for analysis or machine learning. It involves steps such as handling missing values, removing duplicates, normalizing or scaling data, and encoding categorical variables. Proper data preprocessing helps improve the quality and performance of predictive models by ensuring the data is accurate, consistent, and suitable for analysis.
What are the key skills and qualifications needed to thrive as a data preprocessing specialist, and why are they important?
To thrive as a Data Preprocessing Specialist, you need a strong background in statistics, data cleaning, and data transformation, often supported by a degree in computer science, data science, or a related field. Proficiency with tools such as Python (pandas, NumPy), SQL, and data visualization platforms is typically essential, along with familiarity with data management systems. Attention to detail, problem-solving abilities, and effective communication are standout soft skills in this position. These skills are crucial for ensuring high-quality, reliable datasets that underpin accurate data analysis and machine learning outcomes.
What are some common challenges faced in a data preprocessing role, and how can they be effectively managed?
Professionals in Data Preprocessing often encounter challenges such as handling incomplete or inconsistent data, managing large datasets, and ensuring data quality before analysis. Addressing these issues typically involves using specialized tools to automate data cleaning, establishing clear data validation rules, and collaborating closely with data engineers and analysts. Staying updated with best practices and leveraging scripting languages like Python or R can also streamline the preprocessing workflow, making it easier to deliver reliable and accurate datasets for downstream analysis.
What is the difference between Data Preprocessing vs Data Analysis?
| Aspect | Data Preprocessing | Data Analysis |
|---|---|---|
| Primary Focus | Cleaning, transforming, and preparing raw data for analysis | Interpreting data to extract insights and support decision-making |
| Skills Required | Data cleaning, scripting, understanding of data formats | Statistical analysis, data visualization, critical thinking |
| Work Environment | Data engineering teams, data science projects | Business intelligence, research, data science teams |
| Tools Used | Python, R, SQL, ETL tools | Excel, Tableau, R, Python, statistical software |
While data preprocessing involves preparing raw data for analysis by cleaning and transforming it, data analysis focuses on interpreting the prepared data to uncover trends and insights. Both roles are essential in the data pipeline but serve different purposes in the data lifecycle.
What are popular job titles related to Data Preprocessing jobs in California?
For Data Preprocessing jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Preprocessing jobs in California look for?
The top searched job categories for Data Preprocessing jobs in California are:
What cities in California are hiring for Data Preprocessing jobs?
Cities in California with the most Data Preprocessing job openings:
Data Science Chief Expert, Spend
Palo Alto, CA • On-site
SAP
• IT Services • 10K+ employees10,000+ employees
Full-time
Posted 19 days ago
Key responsibilities
Build and scale the semantic and contextual infrastructure that transforms raw business data into knowledge for SAP's AI agents.
Design, maintain, and improve enterprise ontologies and semantic models to enhance data interoperability and business context across various data landscapes.
Develop, evaluate, and operationalize end-to-end machine learning and AI solutions, including data preprocessing, model deployment, and lifecycle support.
Job description
We help the world run better
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging - but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.
The context engine that makes AI enterprise ready.
Anyone can build an AI agent. What makes SAP's agents different is accuracy grounded in the richest enterprise data and process context in the world. As part of our Data and Applied Science team, you'll build the context engine grounded in SAP's Business ontology: the semantic infrastructure that transforms raw business data into the knowledge layer powering SAP's AI agents and assistants.
What you'll build:
The Data and Applied Science team will build the semantic and contextual foundation of SAP's AI. While generic AI agents operate on surface-level patterns, SAP agents are accurate because they understand the real semantics of enterprise business master data, process flows, and domain relationships. You will help build and scale the layer that makes that possible. This may include the following:
What you'll bring:
Required Qualifications
Preferred Qualification
Where you belong:
Join a collaborative, forward-thinking team defining how enterprise AI actually works on a global scale. You'll work alongside curious engineers, thoughtful product minds, and applied researchers all focused on building AI that customers can trust in the highest-stakes business processes. There's room to grow into new technical spaces, ship real impact, and shape SAP's AI future. If you value learning, real ownership, and building foundational infrastructure that matters, you'll feel at home here.
#dlhiring
Bring out your best
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.
We win with inclusion
SAP's culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone - regardless of background - feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.
SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.
For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.
Compensation Range Transparency: SAP believes the value of pay transparency contributes towards an honest and supportive culture and is a significant step toward demonstrating SAP's commitment to pay equity. SAP provides the annualized compensation range inclusive of base salary and variable incentive target for the career level applicable to the posted role. The targeted annual combined range for this position is 274300-609200(USD). The actual amount to be offered to the successful candidate will be within that range, dependent upon the key aspects of each case which may include education, skills, experience, scope of the role, location, etc. as determined through the selection process. Any SAP variable incentive includes a targeted dollar amount and any actual payout amount is dependent on company and personal performance. Please reference this link for a summary of SAP benefits and eligibility requirements: SAP North America Benefits.
We are ethical and compliant
Our leadership credo: Do what's right. Make SAP better for generations to come. We believe that great leadership extends far beyond the mere pursuit of business goals. We value and foster leadership that is driven with purpose and integrity. Our leaders are role models who uphold SAP's values and shape SAP's culture of integrity, by demonstrating and championing ethical and compliant behavior towards all stakeholders.
AI Usage in the Recruitment Process
For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.
Please note that any violation of these guidelines may result in disqualification from the hiring process.
Requisition ID: 459709 | Work Area: Software-Design and Development | Expected Travel: 0 - 20% | Career Status: Executive | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid
Requisition ID: 459709
Posted Date: Aug 26, 2026
Work Area: Software-Design and Development
Career Status: Executive
Employment Type: Regular Full Time
Expected Travel: 0 - 20%
Location:
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging - but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.
The context engine that makes AI enterprise ready.
Anyone can build an AI agent. What makes SAP's agents different is accuracy grounded in the richest enterprise data and process context in the world. As part of our Data and Applied Science team, you'll build the context engine grounded in SAP's Business ontology: the semantic infrastructure that transforms raw business data into the knowledge layer powering SAP's AI agents and assistants.
What you'll build:
The Data and Applied Science team will build the semantic and contextual foundation of SAP's AI. While generic AI agents operate on surface-level patterns, SAP agents are accurate because they understand the real semantics of enterprise business master data, process flows, and domain relationships. You will help build and scale the layer that makes that possible. This may include the following:
- Leverage deep SAP data and process understanding - including SAP data models, metadata structures, and end-to-end business process semantics across Order-to-Cash, Procure-to-Pay, Record-to-Report, and Plan-to-Produce - to build AI and semantic data solutions using SAP master data domains, SAP One Domain Model, SAP Graph API, and SAP Business Accelerator Hub assets.
- Design and maintain enterprise ontologies and semantic models to improve interoperability, entity consistency, and business context across SAP and non-SAP data landscapes, harmonizing sources such as Salesforce, Workday, ServiceNow, MES/IoT systems, and external data providers into unified semantic or analytical layers.
- Work with cloud and data platforms such as Databricks, SAP Datasphere, SAP HANA Cloud, AWS, Azure, or Google Cloud Platform to support reliable AI workflows.
- Translate ambiguous business challenges into concrete AI use cases, technical designs, and measurable business outcomes.
- Design, develop, evaluate, and operationalize end-to-end machine learning and AI solutions - from data preprocessing, feature engineering, experimentation, and validation through to deployment, production handoff, lifecycle support, and continuous improvement.
- Apply advanced methods across machine learning, deep learning, statistical modeling, data mining, optimization, and applied AI to solve enterprise-scale problems.
- Develop AI capabilities - including generative AI and LLM-based solutions - using enterprise business data, knowledge graphs, business process intelligence, and other structured and unstructured data assets.
- Partner closely with product, engineering, business, and customer-facing teams to ensure solutions are scalable, practical, and production-ready.
What you'll bring:
Required Qualifications
- Master's degree or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or related quantitative fields.
- 10+ years of experience to include deep expertise in machine learning, deep learning, statistical modeling, generative AI, and LLMs, with hands-on experience developing, evaluating, and improving models using real-world datasets - including data preprocessing, feature engineering, and experimentation - and strong analytical and mathematical modeling skills.
- 10+ years of experience in machine learning, data science, applied AI, AI research, knowledge engineering, or semantic data systems in industry, research labs, or advanced academic environments.
- Strong Python and SQL skills, including production-grade Python development and experience with ML libraries such as PyTorch, TensorFlow, and scikit-learn.
- Demonstrated experience of deploying, shipping, and operating AI or machine learning solutions in production environments, including production handoff and lifecycle support.
- Experience with big data infrastructure, data processing and transformation tools such as Databricks, and cloud environments such as AWS, Azure, or Google Cloud Platform.
- Excellent communication, collaboration, and customer-facing skills, with significant experience in agile development environments and a strong curiosity for exploring new AI techniques and their practical applications for SAP customers and products.
- Deep working knowledge of SAP data models, metadata structures, and core business processes end-to-end, including how process semantics map to underlying business objects and datasets.
- Hands-on experience with the SAP data and AI platform stack - including SAP Datasphere, SAP HANA Cloud Knowledge Graph Engine, SAP Business Data Cloud, SAP One Domain Model, SAP Graph API, and SAP Business Accelerator Hub - with working knowledge of SAP master data domains and Master Data Governance constructs.
- Hands-on experience designing and maintaining enterprise ontologies using OWL, RDF/RDFS, SKOS, and SHACL, with proficiency in SPARQL, Cypher, and GQL, and experience evaluating trade-offs between RDF triple stores and labeled property graph databases.
- Experience building entity resolution, deduplication, and identity stitching pipelines across SAP and non-SAP systems, with proven ability to harmonize data into a unified semantic layer using federation, virtualization, replication, and shared ontology mapping approaches.
- Understanding data product and data mesh principles, including semantic contracts and governed self-service consumption.
- Proven experience translating abstract business challenges into concrete AI solutions, delivering from concept through production deployment, production handoff, and business adoption.
- Experience working with cross-functional stakeholders - including product, engineering, business, and customer-facing teams - in agile software development environments and enterprise product organizations.
- Experience building AI capabilities using enterprise business data, knowledge graphs, or business process intelligence.
Preferred Qualification
- Experience with Retrieval-Augmented Generation, vector databases, embeddings, semantic retrieval, and enterprise knowledge grounding.
- Experience contributing to reusable AI platforms, foundation model initiatives, shared AI services, or AI capabilities adopted across multiple product areas.
- Experience with agentic AI, reasoning frameworks, planning, orchestration, tool use, or multi-agent architectures.
- Ability to design upper-level and mid-level ontologies aligned with industry standards, map application-specific schemas to shared ontologies using declarative mapping standards and apply semantic interoperability frameworks and canonical business entity models across complex application landscapes.
Where you belong:
Join a collaborative, forward-thinking team defining how enterprise AI actually works on a global scale. You'll work alongside curious engineers, thoughtful product minds, and applied researchers all focused on building AI that customers can trust in the highest-stakes business processes. There's room to grow into new technical spaces, ship real impact, and shape SAP's AI future. If you value learning, real ownership, and building foundational infrastructure that matters, you'll feel at home here.
#dlhiring
Bring out your best
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.
We win with inclusion
SAP's culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone - regardless of background - feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.
SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.
For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.
Compensation Range Transparency: SAP believes the value of pay transparency contributes towards an honest and supportive culture and is a significant step toward demonstrating SAP's commitment to pay equity. SAP provides the annualized compensation range inclusive of base salary and variable incentive target for the career level applicable to the posted role. The targeted annual combined range for this position is 274300-609200(USD). The actual amount to be offered to the successful candidate will be within that range, dependent upon the key aspects of each case which may include education, skills, experience, scope of the role, location, etc. as determined through the selection process. Any SAP variable incentive includes a targeted dollar amount and any actual payout amount is dependent on company and personal performance. Please reference this link for a summary of SAP benefits and eligibility requirements: SAP North America Benefits.
We are ethical and compliant
Our leadership credo: Do what's right. Make SAP better for generations to come. We believe that great leadership extends far beyond the mere pursuit of business goals. We value and foster leadership that is driven with purpose and integrity. Our leaders are role models who uphold SAP's values and shape SAP's culture of integrity, by demonstrating and championing ethical and compliant behavior towards all stakeholders.
AI Usage in the Recruitment Process
For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.
Please note that any violation of these guidelines may result in disqualification from the hiring process.
Requisition ID: 459709 | Work Area: Software-Design and Development | Expected Travel: 0 - 20% | Career Status: Executive | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid
Requisition ID: 459709
Posted Date: Aug 26, 2026
Work Area: Software-Design and Development
Career Status: Executive
Employment Type: Regular Full Time
Expected Travel: 0 - 20%
Location:
About SAP
Sourced by ZipRecruiter
Industry
It services and computer and computer peripheral equipment and software wholesalers
Company size
10,000+ Employees
Headquarters location
Newtown Square, PA, US