We are seeking a highly skilled and motivated Data Scientist to join our Data and Analytics team. This position will develop, implement, and optimize advanced analytics solutions that support data-driven decision-making across the organization.

The ideal candidate will have hands-on experience with Databricks, Microsoft Azure, Snowflake, Python, SQL, machine learning, statistical modeling, data engineering, and ETL pipelines. This role combines data science, data engineering, cloud technologies, and business analytics to solve complex business problems and deliver actionable insights.

Key Responsibilities

Data Science, Analysis, and Modeling

• Develop, implement, and optimize statistical models and machine learning algorithms to solve complex business problems.
• Perform exploratory data analysis (EDA) to identify patterns, trends, relationships, and opportunities within large datasets.
• Conduct feature engineering, data preprocessing, transformation, and validation to prepare datasets for modeling and analysis.
• Evaluate model performance and improve analytical solutions based on business and technical requirements.
• Translate analytical results into actionable business recommendations.

Data Engineering and ETL

• Design, build, maintain, and optimize scalable data pipelines and ETL/ELT processes using Databricks.
• Integrate structured and unstructured data from multiple sources.
• Support data transformation, cleansing, validation, and processing workflows.
• Monitor and improve data quality, accuracy, consistency, and integrity.
• Collaborate with data engineers to develop reliable and scalable data solutions.
• Work with big data technologies and distributed processing frameworks such as Apache Spark.

Azure Cloud and Data Platform

• Utilize Microsoft Azure services to support data ingestion, storage, transformation, processing, and analytics.
• Work with Azure Data Factory (ADF) to develop and maintain data integration and orchestration workflows.
• Work with Azure Data Lake for scalable cloud-based data storage and analytics.
• Develop cloud-based data and analytics solutions following performance, scalability, and data governance best practices.

Snowflake Data Warehouse

• Develop, manage, and optimize data warehouses and data marts in Snowflake.
• Write and optimize SQL queries for data extraction, transformation, analysis, and reporting.
• Improve query performance and ensure efficient data storage and retrieval.
• Support integration between Snowflake, Databricks, Azure, and other enterprise data sources.

Machine Learning and Statistical Analysis

• Apply appropriate machine learning algorithms and statistical methods to business use cases.
• Develop predictive and analytical models using Python, R, and/or Scala.
• Test, validate, and evaluate models using appropriate statistical and machine learning techniques.
• Identify opportunities to use advanced analytics and machine learning to improve business outcomes and operational decision-making.

Collaboration and Communication

• Partner with data engineers, data analysts, business leaders, and other cross-functional stakeholders to understand business and data requirements.
• Translate business problems into technical and analytical solutions.
• Communicate complex analytical findings clearly and concisely to technical and non-technical audiences.
• Present insights, recommendations, and analytical results to business stakeholders.
• Support data-driven decision-making across the organization.

Innovation and Continuous Improvement

• Stay current with emerging trends and advancements in data science, artificial intelligence, machine learning, cloud computing, and big data technologies.
• Identify opportunities to improve existing data, analytics, and machine learning processes.
• Develop innovative solutions that improve efficiency, scalability, and business decision-making.
• Promote best practices for data science, analytics, data engineering, and cloud technologies.

Requirements

Education

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative or technical field.

Experience

• Proven professional experience as a Data Scientist or in a closely related data and analytics role.
• Hands-on experience working with Databricks, Microsoft Azure, and Snowflake.
• Experience developing statistical models and machine learning solutions.
• Experience designing and maintaining data pipelines and ETL/ELT processes.
• Experience working with relational databases, data warehouses, and large datasets.
• Strong proficiency in SQL.
• Proficiency in at least one programming language such as Python, R, or Scala.

Required Skills

• Data Science
• Machine Learning
• Statistical Modeling
• Predictive Analytics
• Python
• SQL
• Databricks
• Microsoft Azure
• Snowflake
• Azure Data Factory
• Azure Data Lake
• ETL/ELT
• Data Pipelines
• Data Engineering
• Data Warehousing
• Data Modeling
• Feature Engineering
• Data Preprocessing
• Exploratory Data Analysis (EDA)
• Data Quality and Data Integrity
• Relational Databases
• Cloud Computing
• Strong analytical and problem-solving skills
• Strong written and verbal communication skills
• Cross-functional collaboration

Preferred Qualifications

• Experience with big data technologies such as Apache Spark and Hadoop.
• Experience with data visualization and business intelligence tools such as Microsoft Power BI or Tableau.
• Certifications in Microsoft Azure, Databricks, or Snowflake.
• Experience working in a similar industry or business domain.
• Experience developing scalable analytics and machine learning solutions in cloud environments.

Preferred Technology Stack

Cloud and Data Platforms: Microsoft Azure, Databricks, Snowflake
Programming: Python, R, Scala
Data and Query Languages: SQL
Data Engineering: ETL/ELT, Data Pipelines, Azure Data Factory, Azure Data Lake
Big Data: Apache Spark, Hadoop
Analytics: Machine Learning, Statistical Modeling, Predictive Analytics, Feature Engineering
Visualization: Power BI, Tableau

About the Role

This position is ideal for a Data Scientist who enjoys working across the full data lifecycle—from data ingestion and engineering through statistical analysis, machine learning, and communicating business insights. The successful candidate will combine strong technical expertise with business acumen and collaboration skills to help the organization maximize the value of its data.

Benefits

Why Join MezTal?

At MezTal, we prioritize innovation, collaboration, and personal growth. You’ll have the opportunity to work on meaningful projects, be part of a supportive team, and enjoy a culture that values work-life balance and professional development.

• Christmas Bonus: 30 days, to be paid in December.
• Major Medical Expense Insurance: Coverage up to $25,000,000.00 MXN.
• Dental Insurance: Always smile with confidence!
• Life Insurance: (Death and MXN Disability)
• Vacation Days: 12 vacation days in accordance with Federal Labor Law + Floating Holidays: 3 floating holidays in addition to the 7 official holidays in Mexico.
• Cell Phone Reimbursement & Transportation Subsidy.
• Multicultural Exposure: Work with operations within Mexico and the United States.
• MezTal Internal Events: Strike a healthy balance between your professional and personal goals.
• Exclusive Discounts: Benefits with different companies for being part of MezTal.
• Academic Agreements: Access to national universities and language schools.