Lead Data Scientist

Summary

Join Blend, an award-winning consultancy, as a Lead Data Scientist to develop advanced recommendation engines and deploy machine learning models. You will leverage your expertise in Python and PySpark, and MLOps to enhance data-driven decision-making. Lead and mentor a team, driving technical excellence and innovation. This role offers the unique opportunity to work 100% remotely if you are currently living in LATAM, or you can join us at the office in Montevideo, Uruguay. The position requires expertise in machine learning, data structures, and statistical modeling techniques. You will collaborate with various teams and stakeholders to ensure the impact and scalability of ML-driven initiatives.

Requirements

• 4+ years of experience in data science or related roles, with a strong focus on recommendation engines
• Expertise in Python and PySpark for data analysis, modeling, and deployment
• Proven experience in MLOps, including deploying models at scale and managing their lifecycle
• Solid understanding of machine learning algorithms, data structures, and statistical modeling techniques
• Experience designing and deploying recommendation engines at scale
• Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders
• Leadership experience in guiding and mentoring a team of data scientists
• Detail-oriented with a passion for building robust, scalable, and efficient machine learning systems
• Excellent written and verbal English for clear and effective communication with the team
• 4+ years of experience in data science, including hands-on work with Generative AI and leadership in team development

Responsibilities

• Design and implement scalable machine learning pipelines with a focus on production-grade reliability and performance
• Collaborate with data engineering and product teams to translate complex business requirements into actionable ML solutions within the Databricks environment
• Lead the end-to-end development of machine learning models—from experimentation and training to deployment, monitoring, and retraining—adhering to MLOps best practices
• Optimize model training and inference workflows using distributed computing in Databricks, ensuring efficient resource usage and minimal latency
• Conduct in-depth performance evaluations and validation strategies, ensuring robustness and fairness of models in production
• Maintain high standards in reproducibility and traceability by leveraging the experiment tracking and lineage features in Databricks
• Partner with stakeholders across business units to align modeling efforts with strategic objectives, ensuring impact and scalability of ML-driven initiatives

Preferred Qualifications

Experience with cloud platforms (AWS, Azure, GCP) and big data technologies is a plus

Benefits

• Every day lunches! (headquarters)
• Vegetarian, vegan, gluten and sugar-free options
• Gourmet meals every Friday with our on-site chef!
• Flexible working options to help you strike the right balance
• All the equipment you need to harness your talent (Macbook and accessories)
• Snacks and beverages available everyday (headquarters)
• After office events, football, tennis and game nights (headquarters)
• Everyone is welcome to join our football league every Wednesday’s and Friday’s
• Challenge your teammates to a pool game and win the office’s trophy!
• Tennis courts available for friendly matches
• You are not a sports person? Don’t worry, we also have chess championships, game and music nights for you to join!
• AWS Certifications (we are AWS Partners)
• Study plans, courses and other certifications
• English Lessons
• Learn from your teammates on our Tech Tuesdays!
• Mentoring and Development opportunities to shape your career path
• Anniversary and birthday gifts
• Great location and even greater teammates!