Data Scientist (Causal Inference & Experimentation)

Data Scientist (Causal Inference & Experimentation)

📍 Mexico | Remote

We are:

Wizeline is a global AI-native technology solutions provider that develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact.

With the right people and the right ideas, there’s no limit to what we can achieve.

Are you a fit?

Sounds awesome, right? Now, let’s make sure you’re a good fit for the role.

We are looking for a Data Scientist with a strong focus on Causal Inference and Experimentation to help drive data-informed decision-making through rigorous statistical analysis and experimental design.

This is a remote role based in Mexico, ideal for candidates who thrive in collaborative, distributed teams and enjoy solving complex business problems through data.

In this role, you will design and evaluate experiments, estimate causal impact, and translate complex analytical findings into clear business insights. You will work closely with cross-functional teams to ensure that strategies are backed by robust evidence and measurable outcomes.

Key Responsibilities

Experimentation & Causal Analysis

• Design and implement Randomized Controlled Trials (RCTs) to rigorously evaluate business strategies and initiatives.
• Ensure sound experimental design, including proper control/treatment group assignment and execution for reliable and reproducible results.
• Estimate causal impact using appropriate statistical techniques (e.g., regression, t-tests, chi-square tests).
• Evaluate assumptions, identify biases, and ensure the robustness of results.

Data Analysis & Insights

• Apply advanced statistical methods to analyze business impact and performance metrics.
• Work with large-scale datasets to extract actionable insights.
• Maintain clear and well-structured documentation of experiments, models, and analytical processes.
• Communicate findings through reports and presentations, translating complex analyses into clear, actionable insights for non-technical stakeholders.

Must-have Skills

• Bachelor’s Degree in Data Science, Statistics, Economics, Mathematics, Engineering, or a related quantitative field.
• 4+ years of experience in data science, with a strong focus on causal inference, experimentation, and impact analysis.
• Advanced English level (written and spoken).
• Strong foundation in statistics, probability, and applied econometrics, including:
• Potential Outcomes framework
• Selection bias and omitted variable bias
• Parallel trends assumption
• Spillover effects and SUTVA
• Proficiency in Python and R for data analysis and causal inference.
• Python libraries: econml, causalml, dowhy, statsmodels, scikit-learn
• R packages: did, fixest, CausalImpact, MatchIt, Synth, gsynth
• Strong experience with SQL and PySpark for large-scale data processing.
• Experience working with the Azure ecosystem, including:
• Databricks
• Azure DevOps
• Ability to design, analyze, and interpret experiments and A/B tests in real-world business contexts.

Nice-to-have

• AI Tooling Proficiency: Leverage one or more AI tools to optimize and augment day-to-day work, including drafting, analysis, research, or process automation. Provide recommendations on effective AI use and identify opportunities to streamline workflows.
• Experience in Consumer Packaged Goods (CPG) or similar industries.
• Ability to thrive in ambiguous and fast-paced environments.
• Familiarity with tools such as Braze and Amplitude for campaign execution and analytics.
• Experience analyzing campaign performance and product engagement metrics.
• Knowledge of best practices in documentation and standardization for experimentation frameworks.

What we offer:

• A High-Impact Environment
• Commitment to Professional Development
• Flexible and Remote Work Culture
• Global Opportunities
• A Vibrant Community
• Total Rewards

*Specific benefits are determined by the employment type and location.

Find out more about our culture here.