15 publicaciones de empleo destacadas de lead software engineering en buenos aires, b (¡Están contratando!)

Senior Associate - Data Science (US Client)
PwC —Buenos Aires, Buenos Aires
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DevSecOps Engineer
Valtech Group —Buenos Aires, Buenos Aires
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Agentic AI Solutions Architect - Remote, Latin America
Bluelight Consulting —Buenos Aires, Buenos Aires
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Industry X - DP&O - MES Analyst/Consultant
Accenture —Buenos Aires, Buenos Aires
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Senior Data Migration [US Client]
PwC —Buenos Aires, Buenos Aires
- Tiempo completo
Senior Net Developer – Híbrido, Montevideo Uy
Web: —Buenos Aires, Buenos Aires
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3d
Java Technical Referent
dLocal —Buenos Aires, Buenos Aires
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10d
Services Engagement Manager
Lenovo —Capital Federal, Buenos Aires
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Cloud Account Executive
Salesforce —Buenos Aires, Buenos Aires
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Product Manager
Emi Labs —Buenos Aires, Buenos Aires
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Sr Salesforce Developer Arg/Brasil/Uruguay
Web: —Buenos Aires, Buenos Aires
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Paid Media Marketing
Darwin AI —Buenos Aires, Buenos Aires
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Prime Named Account Executive - Data Foundation
Salesforce —Buenos Aires, Buenos Aires
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DevOps Sr Remoto
Web: —Buenos Aires, Buenos Aires
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RHEL Sales Specialist
Red Hat, Inc. —Buenos Aires, Buenos Aires
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Senior Associate - Data Science (US Client)

PwC -
Buenos Aires, Buenos Aires

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Detalles del empleo

Tiempo completo

Descripción completa del empleo

Industry/Sector

Not Applicable

Specialism

Actuarial Services

Management Level

Senior Associate

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.

Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

Respond effectively to the diverse perspectives, needs, and feelings of others.
Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
Use critical thinking to break down complex concepts.
Understand the broader objectives of your project or role and how your work fits into the overall strategy.
Develop a deeper understanding of the business context and how it is changing.
Use reflection to develop self awareness, enhance strengths and address development areas.
Interpret data to inform insights and recommendations.
Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.

Minimum years experience required

2 Years

Minimum Educational Qualifications:

Graduated or pursuing Software Engineering or similar IT degree (Technical University Degrees are also to be considered) in Mathematical Statistics, Applied Mathematics, Financial Mathematics, Data Processing/Analytics/Science, Actuarial Science, Operations Management/Research and other related fields of Study may be considered with university degree progress equivalent to at least 3 years.
Preferences: Data Science professionals, Economists, and Actuaries with a specialization in Data Science

Main tasks

Help contribute to the development of GenAI solutions, including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, AI agents, and multi-agent systems (MAS).
Strong statistics knowledge
Experience with programming languages and environments such as Python, R.
Utilize machine learning models.
Design, develop, and deploy AI models in real-world client and business environments.
Monitor and research emerging AI trends, fostering an agile, forward-looking development environment.
Support project delivery and work with clients to process structured and unstructured data to improve business processes, workflows, and decision-making.
Support the documentation and technical analysis efforts for validators, auditors, and regulators; clearly communicate complex concepts to non-technical stakeholders.
Work with cross-functional teams—data engineers, architects, and data scientists—to deliver efficient, high-quality solutions aligned with client needs.
Support business development efforts, including the technical sales cycles and the client proposal process.
Support the development of internal GenAI assets and foundational capabilities to grow the firm’s practice.

Understand the importance of have a correct information management
Knowledge of Information Security and Data Protection
Correct Information Security Management

All qualified applicants will receive consideration for employment at PwC without regard to ethnicity; creed; color; religion; national origin; age; disability; neurodiversity; sexual orientation; gender identity or expression; marital; or any other status protected by law. PwC is proud to be an inclusive organization and equal opportunity employer.

Travel Requirements

Not Specified

Job Posting End Date

June 30, 2026

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Minimum years experience required

2 Years

Minimum Educational Qualifications:

Preferences: Data Science professionals, Economists, and Actuaries with a specialization in Data Science

Main tasks

Help contribute to the development of GenAI solutions, including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, AI agents, and multi-agent systems (MAS).

Strong statistics knowledge

Experience with programming languages and environments such as Python, R.

Utilize machine learning models.

Design, develop, and deploy AI models in real-world client and business environments.

Monitor and research emerging AI trends, fostering an agile, forward-looking development environment.

Support project delivery and work with clients to process structured and unstructured data to improve business processes, workflows, and decision-making.

Support the documentation and technical analysis efforts for validators, auditors, and regulators; clearly communicate complex concepts to non-technical stakeholders.

Work with cross-functional teams—data engineers, architects, and data scientists—to deliver efficient, high-quality solutions aligned with client needs.

Support business development efforts, including the technical sales cycles and the client proposal process.

Support the development of internal GenAI assets and foundational capabilities to grow the firm’s practice.

Understand the importance of have a correct information management

Knowledge of Information Security and Data Protection

Correct Information Security Management