Job description
Company Description
Blend is an award-winning, new breed consultancy focused on powering exceptional results for our Fortune 500⁄1000 clients and other major organizations. We are a growing company—born at the intersection of advanced analytics, data, and technology.
Who we are:
People are everything at Blend. We are inspired by advancing our Client’s most critical initiatives, products and projects by matching our clients with the right talent. BLEND360 has been among the Inc. 5000 fastest growing companies 8 years in a row, and we’re very proud of our World Class NPS score. Our success is a direct result of our passion for advancing the careers of the talented people we work with every day. When you work at Blend, you will:
Collaborate with a smart, passionate group of people who are invested in your sucess.
Partner with an impressive list of clients, who value Blend360’s services and the world class experience we deliver with every engagement.
Thrive with a company and leadership team who are committed to growth.
Job Description
What is this position about?
As a Lead Data Scientist, you will be developing advanced recommendation engines and deploying machine learning models into production environments. Leveraging your expertise in Python and PySpark coding, along with your experience in MLOps, you will play a pivotal role in enhancing our data-driven decision-making processes.
This position offers a unique opportunity to lead and mentor a team while driving technical excellence and innovation in a dynamic, data-centric organization.
You may work 100% remotely if you are currently living in Colombia, Uruguay or Agentina! or you can always join us at the office in Montevideo, Uruguay or Bogotá Colombia!
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.
Qualifications
- 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.
- Experience with cloud platforms (AWS, Azure, GCP) and big data technologies is a plus.
- 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.
Additional Information
⚖️ 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).
📚 Learning opportunities:
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!
So what are the next steps?
We are eager to learn about you! Send us your resume and LinkedIn profile below and we’ll explore working together!
