Data Science Lead

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 with strong knowledge in A/B testing and Analytics to contribute to our next level of growth and expansion.

This position is for an experienced Data Scientist who will design and implement advanced MMM solutions. The Senior Data Scientist will focus on developing robust MMM ---while leveraging strong expertise in modeling, Python, and SQL. 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

As a Lead Data Science you will be able to contribuite and build on one of our most interesting projects, among your tasks you will find

• Design, execute, and analyze A/B and multivariate experiments to drive data-informed decision-making across products and features.

• Develop scalable and statistically sound experimentation frameworks, ensuring proper randomization, metric definition, and power analysis.

• Collaborate with product managers, engineers, and analysts to embed experimentation into the product development lifecycle.

• Build reusable tools and libraries for experiment tracking, analysis, and reporting.

• Ensure validity of experiment results through rigorous diagnostic checks, bias correction, and guardrail metrics.

• Drive a culture of experimentation across the organization by establishing best practices, documentation, and training programs.

• Stay current on causal inference, uplift modeling, and experimentation methodologies to continuously refine our testing capabilities.

Qualifications

• 5+ years of experience in data science or related roles, with a strong focus on recommendation engines.

• Strong foundation in statistical techniques including hypothesis testing, confidence intervals, regression modeling, and causal inference.

• Expertise in designing and analyzing controlled experiments (A/B, multivariate, geo-testing, etc.) at scale.

• Proven programming skills in Python or R for data manipulation, analysis, and visualization.

• Experience working with experiment platforms and telemetry/data instrumentation pipelines.

• Proficiency with SQL and relational databases for pulling and analyzing experiment data.

• Familiarity with business metrics and KPIs for product, growth, or marketing experiments.

• Experience implementing uplift modeling, CUPED, and other variance-reduction or bias-correction techniques.

• Exposure to Bayesian experimentation frameworks (e.g., using PyMC, Stan, or similar) is a strong plus.

Additional Information

⚖️ Flexible working options to help you strike the right balance.

👨🏽‍💻 All the equipment you need to harness your talent.

🎮After office events, football, tennis and game nights (on headquarters).

📚 Learning opportunities:

• AWS Certifications (we are AWS Partners).

• Study plans, courses and other certifications.

• English Lessons.

👩‍🏫 Mentoring and Development opportunities to shape your career path.

🏡 Great location and even greater teammates!

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