Senior Machine Learning Engineer

Arionkoder; Buenos Aires; Remote; ARS 92,909,000 - 139,364,000; Full time

Benefits offered by this job

10 days PTO

USA holidays

100% remote

Job summary

Prometeo Talent partners with a U.S.-based company to hire a Data Analyst (Machine Learning) for remote work across LATAM. The role emphasizes turning large-scale consumer data into clear metrics, with strong SQL and Python skills and the ability to communicate results to stakeholders in English.

The position welcomes recent graduates and mid-level analysts, offering exposure to marketing effectiveness measurement and cross-border teamwork with international stakeholders.

Qualifications

• 0 to 4 years of experience in Data Analysis or similar roles.
• Advanced English level (written and spoken).
• Foundational to intermediate SQL skills including joins and CASE WHEN.
• Python for data cleaning and processing with pandas.
• Experience with text data cleaning and parsing.
• Bachelor's degree in relevant field with quantitative coursework.

Responsibilities

• Write, optimize, and execute SQL queries to extract data from relational databases and cloud data warehouses.
• Develop, run, and validate machine learning, predictive, or statistical models to uncover consumer behaviors and forecast trends.
• Slice and aggregate raw data to calculate market shares, penetration, and purchasing trends.
• Build and maintain clean data tables and views for recurring reports and dashboards.
• Review outputs, perform data audits, and ensure data integrity before insights are shared.
• Translate results into clear summaries for stakeholders in English-speaking environments.

Skills

SQL

Python

English

Data analysis

Pandas

Machine Learning

Education

Bachelor's degree in relevant field

Tools

Snowflake

BigQuery

Redshift

Job description

Machine Learning Analyst | 100% Remoto | LATAM

What do we offer?

Prometeo Talent is a recruitment agency with a strong presence across the Americas and Europe. We specialize in connecting companies with exceptional professionals across data, analytics, and business functions.

We have partnered with a U.S.-based company specialized in marketing effectiveness measurement. They help organizations better understand consumer behavior, purchasing trends, brand performance, and market dynamics through data-driven insights.

We are looking for a Data Analyst (Machine Learning) to join our client's global team.

This role is ideal for analytical and data-driven professionals who enjoy working with large-scale consumer and retail datasets, bridging the gap between complex database structures and business strategy, and turning raw transactional or behavioral data into clear, actionable metrics.

The ideal candidate combines solid SQL and Python skills, a strong "numbers sense", attention to detail, and the ability to translate technical results into clear summaries for stakeholders in English. The position is open to a range of experience levels, from recent graduates with a strong quantitative background to mid-level analysts looking to deepen their technical data manipulation skills.

What You Will Do

• Write, optimize, and execute SQL queries to extract data from relational databases and cloud data warehouses.
• Develop, run, and validate machine learning, predictive, or statistical matching models to uncover deeper consumer behaviors and forecast trends.
• Slice, unpivot, and aggregate raw transactional or panel data to calculate core business metrics such as household penetration, market share, and purchasing trends.
• Build and maintain clean, structured data tables and views that feed into recurring tracking reports and stakeholder dashboards.
• Review query outputs, perform data audits, and double-check logic to ensure accuracy and data integrity before insights are finalized.
• Use conditional logic and filtering techniques to segment data and isolate specific tracking cohorts.
• Clean, parse, and categorize unstructured or semi-structured text data.
• Translate technical data structures and query results into clear written summaries, bullet points, or data tables for stakeholders in English-speaking environments.

Requirements

• 0 to 4 years of experience in Data Analysis, Business Analytics, or similar roles. Entry-level candidates with strong relevant coursework, personal data projects, or internships are welcome, as well as mid-level professionals with a proven track record of querying databases to drive business insights.
• Advanced English level (written and spoken).
• Foundational to intermediate SQL skills, including complex JOIN logic, standard aggregations, and CASE WHEN conditional logic.
• Python scripting for data cleaning, manipulation, and processing, with proficiency in pandas for complex multi-step transformations.
• Familiarity with modeling libraries such as scikit-learn or statsmodels to build and evaluate predictive or statistical matching models.
• Experience working with messy text fields: cleaning, parsing, filtering, and pattern matching within string variables.
• Solid understanding of relational database design, including how tables connect, primary/foreign keys, and data normalization.
• Bachelor's degree in Business Analytics, Statistics, Mathematics, Computer Science, Economics, Marketing, or a related field with coursework covering database management or quantitative data analysis.

Nice to Have

• Experience working with consumer, retail, panel, or transactional datasets.
• Familiarity with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift).
• Exposure to marketing analytics, consumer insights, or market measurement environments.
• Experience building data tables or views that feed dashboards and recurring reports.

Why Join Us?

10 days of PTO to recharge wherever you choose.
Enjoy USA Holidays.
100% remote work—design the work-life balance that fits you best.
Work with real consumer and market data that influences strategic business decisions.
Collaborate with international teams and stakeholders.
Develop your expertise in SQL, Python, and machine learning while working on impactful projects.