1 день назад
Senior Data Scientist Lead (AWS)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Scientist Lead (AWS): Leading the design, development, and delivery of data science and machine learning solutions across the full lifecycle with an accent on statistical modeling, cloud-based AWS environments, and technical leadership. Focus on building production models, optimizing performance, mentoring data professionals, and translating complex business challenges into scalable data-driven solutions.
Location: Argentina, Uruguay, or Brazil; fully remote
Employment type: Contract
Company
designs and delivers scalable digital solutions for global companies, combining technical expertise with a product mindset to lead complex software initiatives end to end.
What you will do
- Lead the design and implementation of data science initiatives, methodologies, technical approaches, and best practices.
- Develop, evaluate, and optimize statistical and machine learning models for complex business problems.
- Own the full data science lifecycle, including data exploration, feature engineering, validation, deployment, monitoring, and continuous improvement.
- Design scalable data science and machine learning solutions using AWS cloud services.
- Provide technical guidance, mentor data professionals, conduct technical reviews, and promote knowledge sharing.
- Collaborate with business stakeholders, product teams, data engineers, and software engineers to deliver data-driven solutions.
Requirements
- 6+ years of professional experience in data science, machine learning, advanced analytics, or a related field, including technical leadership experience.
- Strong hands-on expertise in statistical modeling, machine learning algorithms, predictive analytics, experimentation, and data-driven problem solving.
- Advanced proficiency in Python and strong SQL skills, with experience working with large datasets and data warehouses.
- Strong knowledge of supervised and unsupervised learning, model evaluation, feature engineering, optimization, and production machine learning practices.
- Hands-on experience designing or implementing data science and machine learning solutions in AWS environments.
- Advanced English proficiency required for communication with international teams, stakeholders, and leadership.
Nice to have
- Experience with AWS SageMaker, S3, Glue, Redshift, Lambda, EMR, or Athena.
- Production machine learning deployment and monitoring experience, including MLOps and ML lifecycle automation.
- Experience with Spark, Docker, Kubernetes, Generative AI, LLMs, RAG, or NLP.
- AWS certifications or experience in financial services and other data-intensive industries.
Culture & Benefits
- 100% remote work within the stated locations.
- Long-term engagement with international clients.
- Opportunity to influence data science and machine learning strategy.
- Collaborative international environment with experienced technical teams.
- Continuous learning and professional growth opportunities.
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