Data Science Lead

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, along with MLOps experience, to enhance data-driven decision-making. This role offers leadership and mentorship opportunities within a dynamic organization. You can work 100% remotely from Colombia, Uruguay, or Argentina, or work from the office in Montevideo, Uruguay or Bogotá, Colombia. The position involves designing and implementing scalable machine learning pipelines, collaborating with various teams, and optimizing model workflows. You will also conduct performance evaluations and ensure model robustness, while partnering with stakeholders to align modeling efforts with strategic objectives.

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

Responsibilities

• Develop advanced recommendation engines and deploy machine learning models into production environments
• Leverage your expertise in Python and PySpark coding, along with your experience in MLOps, to enhance our data-driven decision-making processes
• Lead and mentor a team while driving technical excellence and innovation in a dynamic, data-centric organization
• 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

• Flexible working options to help you strike the right balance
• All the equipment you need to harness your talent
• Snacks and beverages available everyday (headquarters)
• After office events, football, tennis and game nights (headquarters)
• 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
• Great location and even greater teammates!