
Data Scientist II
Há 5 dias
We are hiring multiple Data Scientists across LATAM to join the Microsoft 365 team. These are remote positions, allowing you to work from the comfort of your home
As part of our team, you will help shape one of Microsoft’s fastest-growing cloud services. Your work will directly impact Copilot, enabling personalized, context-aware experiences that empower millions of users across Microsoft 365.
Do you want to collaborate closely with software engineers, product managers, and researchers to design, implement, and evaluate models and algorithms that continuously adapt and improve based on user interactions and feedback? Do you want to leverage advanced machine learning and information retrieval to predict and optimize memory content selection, representation, and lifecycle management.
You will work at the forefront of applied AI and machine learning, shaping the future of intelligent productivity tools. You will contribute to a culture of innovation, continuous learning, and experimentation.
Responsibilities- Develop and evaluate ML models using prepared datasets, customer feedback, and novel training/fine-tuning algorithms for language models.
- Write production-quality code, apply debugging best practices, and stay current with industry trends.
- Drive customer-centric solutions by aligning with business goals and managing stakeholder expectations.
- Collaborate cross-functionally to define success metrics and improve AI quality at scale.
- Lead research projects that yield new algorithms, tools, or insights solving open problems.
- Analyze evaluation outputs to identify gaps in coverage, quality, and usability.
- Design experiments, define metrics, and develop ML pipelines for encoder-decoder and cross-encoder models, semantic search, and user intent understanding.
- Work with large-scale data while championing privacy and compliance.
- Engage with customers and internal teams to identify pain points and drive impactful improvements.
- Stay engaged with the latest research and foster a strong applied science culture. Publishing is encouraged.
- Bachelor’s degree in Statistics, Econometrics, Computer Science, Electrical/Computer Engineering, or related field.
- 4+ years of experience in predictive analytics, statistics, or research.
- Experience with synthetic data generation and data management for evaluation/training.
- At least one year of experience publishing patents or peer-reviewed papers.
- Deep motivation for user-centric AI and interest in human cognition, memory, and AI.
- Global collaboration is integral to our work at Microsoft, and proficiency in English is essential for effective communication in this role.
- Master’s degree in Statistics, Econometrics, Computer Science, Electrical/Computer Engineering, or related field.
- Experience with large-scale embedding models and transformer architectures.
- Familiarity with reinforcement learning and distributed computing platforms (e.g., Heron, AML, Euclid).
- Proficient analytical skills and experience with telemetry and performance metrics.
- DevOps experience and cloud services knowledge (Azure preferred).
- Agile development experience and a structured approach to software design.
- Growth mindset with resilience and a passion for learning.
- Commitment to diversity, inclusion, and authentic collaboration.
- Effective communication skills with the ability to engage diverse audiences.
- Ownership mindset with the ability to deliver results and manage expectations.
- Self-motivated and collaborative across teams and organizations.
Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances.
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