Senior Data Scientist

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com We are seeking a Senior Data Scientist to contribute to our next level of growth and expansion. What is this position about? We are seeking a Senior Data Scientist with strong experience in Recommendation Systems and a solid understanding of Machine Learning and MLOps. The ideal candidate will be responsible for developing and improving recommendation solutions, integrating LLM-based capabilities when applicable, and taking machine learning solutions from experimentation and development through production. This role requires strong technical expertise in Python and SQL, experience with cloud technologies, and the ability to work effectively across the data science and engineering lifecycle. Design, develop, and optimize machine learning models and recommendation systems for real-world business applications. Develop recommendation solutions focused on relevance, personalization, and measurable business impact. Work with large datasets using Python and SQL to explore data, develop features, train models, and evaluate results. Integrate LLM-based capabilities and services into existing or new machine learning solutions when appropriate. Apply MLOps practices to support the deployment, monitoring, maintenance, and continuous improvement of machine learning models. Take data science solutions from experimentation and prototyping through production. Collaborate with Data Scientists, Data Engineers, Software Engineers, and other stakeholders to deliver production-ready solutions. Leverage cloud technologies and tools such as Docker and Kubernetes to support scalable machine learning applications. Evaluate model performance, identify opportunities for improvement, and communicate technical decisions and trade-offs. Contribute to best practices around machine learning development, deployment, reproducibility, and productionization. Proven experience as a Data Scientist, with strong experience developing Machine Learning solutions. Strong knowledge of Recommendation Systems and related modeling approaches. Strong programming skills in Python. Strong SQL skills and experience working with data at scale. Hands-on experience taking Machine Learning models and solutions into production. Solid understanding of MLOps principles and practices. Experience working with cloud-based technologies and environments. Experience with Docker and Kubernetes. Experience integrating LLMs or LLM-based services into data science or machine learning solutions. Strong analytical and problem-solving skills. Ability to communicate technical concepts clearly to both technical and non-technical stakeholders. Ability to work collaboratively in a multidisciplinary environment. What about languages? Advanced English proficiency is required, with the ability to communicate technical concepts clearly and effectively in a professional environment. Our Perks and Benefits: 📚 Learning Opportunities: Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. Access to AI learning paths to stay up to date with the latest technologies. Study plans, courses, and additional certifications tailored to your role. Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. English lessons to support your professional communication. 👩‍🏫 Mentoring and Development: Career development plans and mentorship programs to help shape your path. 🎁 Celebrations & Support: Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. Company-provided equipment. ⚖️ Flexible working options to help you strike the right balance. Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.