Company Description
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?
This position is for an experienced Data Scientist who will design and implement advanced machine learning solutions within Snowflake. The Senior Data Scientist will focus on developing robust MLOps practices—including feature stores, model registry, pipelines, testing, and deployment governance—while leveraging strong expertise in ML modeling, Python, and PySpark. This is a senior-level role for an individual contributor who takes ownership of complex projects, but it does not include direct people management. The position is open to candidates located in Argentina, Colombia, Chile or Uruguay.
Job Description
Develop and deploy scalable machine learning models using Python and PySpark.
Build and implement end-to-end MLOps frameworks within Snowflake, including feature stores, model registry, and pipelines.
Define and enforce best practices for model testing, monitoring, and deployment governance.
Collaborate with data engineers, product teams, and business stakeholders to deliver actionable ML solutions.
Conduct model validation and performance evaluation, ensuring fairness, robustness, and reproducibility.
Drive efficiency and scalability in ML workflows through automation and distributed computing.
Stay up to date with emerging trends in ML, MLOps, and Snowflake ecosystem to continuously improve solutions.
Qualifications
Strong expertise in machine learning modeling and algorithm development.
Advanced proficiency in Python and PySpark for large-scale data analysis and ML workflows.
Hands-on experience with Snowflake for data processing and ML pipeline implementation.
Exposure to MLOps practices (model deployment, lifecycle management, governance).
Solid problem-solving and communication skills, with the ability to engage technical and non-technical stakeholders.
Experience collaborating across teams in data-intensive environments.
Familiarity with cloud platforms (AWS, Azure, or GCP) is a plus.
What about languages?
Excellent written and verbal English is required to ensure effective communication with team members and stakeholders.
How much experience must I have?
Minimum of 5+ years of experience in Data Science, with proven expertise in ML modeling and applied MLOps practices.
Additional Information
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.
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.
