דרושים מדען נתונים ב-Paypal ב-India, Chennai

Essential Responsibilities:

• Lead advanced data analysis projects, applying statistical models and predictive techniques.
• Mentor junior analysts and provide guidance on best practices in analytics.
• Develop actionable insights and recommendations for senior business stakeholders.
• Design, build, and maintain advanced dashboards and data visualizations.
• Partner with business leaders to identify new opportunities for data-driven improvements.

Expected Qualifications:

• 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

• Strong analytical understanding and problem-solving skills.
• Proficiency in SQL for querying and managing data.
• Advanced knowledge of Excel (pivot tables, formulas, macros).
• Hands-on experience with Tableau , Looker , and PowerPoint for reporting and visualization.
• Ability to present complex data in a clear and concise manner.
• High attention to data accuracy and detail.

Belonging at PayPal:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Design and develop data pipelines for efficient data collection and processing.
• Build and maintain scalable data storage solutions.
• Ensure data quality and consistency through validation and cleansing processes.
• Implement data transformation techniques to prepare data for analysis.
• Collaborate with cross-functional teams to understand data requirements and provide solutions.
• Optimize data engineering processes for performance and reliability.

Expected Qualifications:

• 1+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

• Design, build, and maintain efficient ETL/ELT pipelines to process large volumes of data
• Develop and optimize data workflows using modern data engineering tools and frameworks
• Ensure data quality, reliability, and performance across all data processing systems
• Monitor and troubleshoot data pipeline issues, implementing proactive solutions

• Create and maintain data models that support analytics and reporting requirements
• Work with BigQuery and other cloud data platforms to optimize data storage and retrieval
• Implement data governance best practices and ensure compliance with data standards
• Collaborate on data architecture decisions and technical design reviews

• Partner with data scientists, analysts, and business stakeholders to understand data requirements
• Participate in agile development processes and contribute to team planning and retrospectives
• Share knowledge and mentor junior team members
• Stay current with emerging data technologies and industry best practices

• SQL Expertise: Advanced proficiency in SQL for complex data manipulation, optimization, and analysis
• BigQuery: Hands-on experience with Google BigQuery, including query optimization and cost management
• Programming: Proficiency in Python or other scripting languages for data processing and automation
• ETL Knowledge: Solid understanding of ETL concepts, tools, and best practices
• Data Modeling: Experience with dimensional modeling, data warehousing concepts, and schema design

• 2-4 years of experience with 1+ years of relevant experience in data engineering or related field
• Strong problem-solving abilities and attention to detail
• Excellent communication skills and ability to explain technical concepts to non-technical stakeholders
• Experience working in collaborative, cross-functional team environments

• Experience with cloud platforms (Google Cloud Platform, AWS, or Azure)
• Knowledge of data orchestration tools (Apache Airflow, Prefect, or similar)
• Familiarity with streaming data technologies (Apache Kafka, Pub/Sub)
• Experience with version control systems (Git) and CI/CD practices
• Understanding of data security and privacy principles
• Bachelor's degree in Computer Science, Engineering, or related field

• Genuine enthusiasm for working as part of a team
• Willingness to share knowledge and learn from others
• Positive attitude and constructive approach to problem-solving
• Ability to give and receive feedback effectively

• Eagerness to learn new technologies and methodologies
• Adaptability to changing business requirements and technical landscapes
• Initiative to propose improvements and innovative solutions
• Commitment to personal and professional development

• Opportunity to work with cutting-edge data technologies
• Collaborative and supportive team environment
• Professional development and learning opportunities
• Competitive compensation and benefits package
• Flexible work arrangements

Our Benefits:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Lead the design and development of complex data pipelines for data collection and processing.
• Develop and maintain advanced data storage solutions.
• Ensure data quality and consistency through sophisticated validation and cleansing processes.
• Implement advanced data transformation techniques to prepare data for analysis.
• Collaborate with cross-functional teams to understand data requirements and provide innovative solutions.
• Optimize data engineering processes for performance, scalability, and reliability.

Expected Qualifications:

• 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

• Strong proficiency in BigQuery , Hadoop , and Big Data ecosystems .
• Experience with GCP services (Dataflow, Pub/Sub, Cloud Storage).
• Advanced knowledge of SQL and data modeling.
• Familiarity with ETL tools and data pipeline automation .
• Problem-solving skills and ability to work in agile environments .

Belonging at PayPal:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Lead the configuration, maintenance, and optimization of the organization's network and security infrastructure to ensure high performance and reliability.
• Architect and integrate networks across multiple business units and diverse cloud environments, ensuring seamless connectivity and scalability.
• Champion the use of Infrastructure as Code processes to automate and maintain infrastructure consistency, scalability, and up-to-date configurations.
• Oversee the configuration, deployment, and management of F5 Local Traffic Managers (LTMs) and Advanced Security Modules (ASMs) to ensure seamless application delivery and security.
• Create and implement strategies for integrating cloud Virtual Private Clouds (VPCs), interconnects, and direct connects, ensuring efficient and secure data flow between on-premises and cloud environments.
• Proactively identify opportunities to enhance the network’s scalability and resilience, ensuring it can handle growing business demands and traffic loads.
• Work closely with infrastructure, application, and security teams to ensure network designs meet cross-functional requirements and adhere to best practices.

Minimum Qualifications:

• Minimum of 8 years of relevant work experience and a Bachelor's degree or equivalent experience.

Preferred Qualification:

• Master's degree or higher in Computer Science, Mathematics, or related field with keen interest in Machine Learning and AI
• Proven experience in developing and implementing solutions in machine learning and AI-related spaces
• Strong programming skills in languages such as Python, Java, or C++
• In-depth knowledge of machine learning frameworks and libraries for analytics and text processing (e.g., TensorFlow, PyTorch)
• Experience with cloud services related to machine learning (Vertex AI, etc.)
• Excellent problem-solving skills and the ability to work in a fast-paced environment
• Strong communication skills to effectively collaborate with team members and stakeholders
• Strong knowledge of algorithms, statistics, data structures, distributed systems, and software engineering best practices
• Proven experience leading and delivering complex ML projects at production scale
• Experience integrating ML solutions into cloud environments (e.g., AWS, Azure, GCP) is highly desirable
• Perform model tuning, evaluation, and monitoring for performance and accuracy improvements.
  Provide mentorship and guidance to junior developers and contribute to code reviews, technical design sessions, and project planning.
  Ensure security, scalability, and performance of ML models deployed in production.

Our Benefits:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Lead the design and development of complex data pipelines for data collection and processing.
• Develop and maintain advanced data storage solutions.
• Ensure data quality and consistency through sophisticated validation and cleansing processes.
• Implement advanced data transformation techniques to prepare data for analysis.
• Collaborate with cross-functional teams to understand data requirements and provide innovative solutions.
• Optimize data engineering processes for performance, scalability, and reliability.

Minimum Qualifications:

• Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.

into a, enabling seamless data access foracross the enterprise.

Minimum Qualifications:

• 8-10 years of relevant work experience and a Bachelor's degree or equivalent experience.

Required Skills:

• Software Development Expertise – Strong proficiency in back-end (Java or Python) technologies, including building and maintaining scalable services. Having front-end (React, Angular, JavaScript, HTML, CSS) experience is an advantage.
• Data Engineering & Cloud Technologies – Experience working with databases (Oracle, MySQL, PostgreSQL) , Big Data technologies (Hadoop, Spark, Kafka, ElasticSearch/Solr) , and cloud platforms (AWS, GCP, Azure) .
• Scalability, Performance & Security – Deep understanding of designing systems for high availability, performance, and security , preferably in regulated industries like financial services.

Travel Percent:

.

Our Benefits:

.

.

Any general requests for consideration of your skills, please.

Essential Responsibilities:

• Design and develop data pipelines for efficient data collection and processing.
• Build and maintain scalable data storage solutions.
• Ensure data quality and consistency through validation and cleansing processes.
• Implement data transformation techniques to prepare data for analysis.
• Collaborate with cross-functional teams to understand data requirements and provide solutions.
• Optimize data engineering processes for performance and reliability.

Minimum Qualifications:

• Minimum of 2 years of relevant work experience and a Bachelor's degree or equivalent experience.

Your day-to-day

• Work with large datasets to support the development and maintenance of data pipelines that help monitor key business metrics and generate valuable insights for decision-making.

• Assist in implementing data quality checks and monitoring solutions to ensure data integrity, consistency, and reliability across key pipelines.

• Collaborate with senior engineers in maintaining and enhancing the data infrastructure, ensuring automation and efficiency in data processing workflows.

• Contribute to projects focused on risk management and process optimization by applying data-driven solutions to solve specific business problems.

• Carry out assignments with moderate complexity under guidance, while continuously looking for ways to improve data processes and outputs.

• Develop a working knowledge of the business domain to support data initiatives within a broader strategic context.

• Support communication with cross-functional teams to clarify requirements, share updates, and align on project goals.

• Collaborate with analysts and other stakeholders to help uncover insights that support operational and business decisions.

• 2–5 years of experience in data engineering, working with large-scale data processing systems.

• Strong experience in BigQuery, SQL, Python, and knowledg of Spark. Familiarity with Google Cloud Platform services such as BigQuery, Cloud Storage, Dataflow, or Dataproc is a plus.

• Good understanding of data modeling concepts and ability to document data workflows effectively.

• Experience participating in Business Intelligence and data pipeline projects, including gathering requirements and analyzing structured data sets.

• Comfort with statistical thinking, attention to detail, and a problem-solving mindset.

• Exposure to domains like payments, e-commerce, or financial services is beneficial but not required.

• Self-driven and enthusiastic about learning and growing within a fast-paced environment. Able to work well both independently and as part of a team.

• Strong communication skills, with the ability to collaborate across teams and present findings clearly.

• Organized and thoughtful, with a focus on execution and follow-through on assigned tasks

Our Benefits:

Any general requests for consideration of your skills, please

Your day to day

• Extract, prepare, and validate large, complex datasets from PayPal’s proprietary systems using SQL, Python to support model development and analytics.

• Build, enhance, and document CECL/IFRS9-compliant loss prediction models, leveraging PD/EAD/LGD frameworks and vintage loss rate methodologies.

• Conduct rigorous model performance testing, stress testing, and scenario analysis to ensure models are robust and regulatory-compliant

• Collaborate cross-functionally with implementation, finance, accounting, risk, and external stakeholders to align on model outputs, definitions, and business needs.

• Clearly communicate analytic insights and model results to senior leadership, and provide expert support for regulatory exams and audit reviews.

What do you need to bring

• Advanced degree in a quantitative discipline (e.g., statistics, mathematics, data science, computer science, engineering, or related field).

• Deep expertise in statistical modeling, machine learning, or econometrics applied to credit risk, knowledge and familiarity of CECL and IFRS9 regulatory requirements and modeling best practices is a plus.

• Strong technical skills working with large datasets using SQL, Python, R, or similar tools; experience with cloud-based platforms such as GCP is highly desirable.

• 5+ years of hands-on experience developing consumer or small business credit risk models, preferably within a CECL/IFRS9 framework.

• Excellent communication and collaboration skills, with strong business judgment and a passion for data-driven problem solving.

Our Benefits:

Any general requests for consideration of your skills, please