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BBVA
BBVA
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BBVA एक वैश्विक बैंकिंग और वित्तीय सेवा समूह है, जो लोगों और व्यवसायों के धन प्रबंधन के तरीके को आधुनिक बनाने के लिए काम करता है। इसकी गतिविधियों में कॉर्पोरेट और निवेश बैंकिंग, फिनटेक और डिजिटल बैंकिंग शामिल हैं। यह प्रौद्योगिकी-सक्षम वित्तीय समाधानों के माध्यम से 7.15 करोड़ ग्राहकों को सेवाएँ प्रदान करता है। 1,21,000 से अधिक कर्मचारियों के साथ, BBVA बैंकिंग, परामर्श और मार्केटिंग के विशेषज्ञों को एक सहयोगी वातावरण में साथ लाता है, जो नवाचार, डिजिटल रूपांतरण और पेशेवर उत्कृष्टता पर केंद्रित है।
LinkedIn
कंपनी की नौकरियाँ

Senior Data Scientist, Mexico City (Hybrid)

At BBVA, shape governed machine-learning solutions for a global banking environment. Establish technical architectures, evaluation standards, reusable practices, and expert guidance for data-science teams.

MXमैक्सिकोहाइब्रिडपूर्णकालिकवरिष्ठआवश्यक भाषा: स्पेनिशडेटा वैज्ञानिक
AWSPySparkPythonSparkSQLक्लाउड

विवरण

  • Define technical patterns, standards, architectures, and evaluation frameworks for Data Science solutions
  • Lead or assess high-impact technical decisions across Machine Learning, graph technologies, Deep Learning, NLP, GenAI, and related specialties
  • Design assessments covering model performance, quality, explainability, bias, security, limitations, and monitoring
  • Review technically complex or materially risky cases, documenting findings, alternatives, decisions, and remediation actions
  • Develop reusable components, libraries, guides, evaluations, and patterns, and support their adoption
  • Mentor Associates and Experts while leading advanced technical sessions
  • Partner with Managers, governance leaders, product teams, and business stakeholders to align value, quality, risk, and regulatory compliance
  • Provide expert direction on technical decisions where established patterns do not exist
  • Turn specialized knowledge into adoptable standards while maintaining experimental rigor, traceability, governance, and business alignment

आवश्यकताएँ

  • Advanced proficiency in Python
  • Deep experience with Machine Learning and model evaluation
  • Demonstrable expertise in at least one area such as graph technologies, Deep Learning, NLP, GenAI, or recommendation systems
  • Experience processing and analyzing data with Spark, PySpark, SQL, and large-scale data ecosystem tools
  • Background in experimental design, baseline comparison, model validation, and limitation documentation
  • Knowledge of model-governance practices including versioning, traceability, documentation, risk controls, and monitoring
  • Ability to design architectures, technical patterns, or reusable assets and support their adoption
  • Experience working in cloud environments, preferably AWS
  • Experience with MLOps, CI/CD, model deployment, and model monitoring
  • Knowledge of LLMs, RAG, generative-system evaluation, guardrails, and responsible AI techniques
  • Participation in technical communities, publications, library contributions, or specialized training
  • Bachelor’s degree in Mathematics, Engineering, Actuarial Science, Computer Science, Data Science, or a related field
  • 8 to 12 years of experience in Data Science
  • Evidence of applying or piloting standards, evaluations, patterns, or technical assets in at least two contexts
  • Sustained experience providing technical mentoring

लाभ

  • Reasonable accommodations throughout the selection process
  • A collaborative and inclusive work environment
  • Commitment to diversity, inclusion, and equal opportunity

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