Senior Ml Ops Engineer - Remote Cloud & Ci/Cd

Oyster

Santa Fe Capital

Remote

ARS 69,181,000 - 107,614,000

Full time

5 days ago
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Benefits offered by this job

10 days PTO
US Holidays
100% remote

Job summary

Prometeo Talent is partnering with a U.S.-based company to recruit a Data Analyst (Machine Learning) to join the client’s global team. The role focuses on large-scale consumer and retail datasets, turning raw data into actionable metrics and requiring strong SQL and Python skills with clear English communication.

The position welcomes candidates from recent graduates to mid-level analysts who want to deepen data manipulation skills and work on impactful ML projects in a 100% remote LATAM setup.

Qualifications

  • Bachelor's degree or higher in a quantitative/analytics field.
  • Solid SQL skills with complex JOINs and CASE WHEN.
  • Proficient Python for data cleaning and transformations (pandas).
  • Experience building ML or predictive models and validating results.

Responsibilities

  • Write, optimize, and execute SQL queries for data extraction from databases and data warehouses.
  • Develop and validate machine learning, predictive, or statistical models to uncover insights and forecast trends.
  • Slice and aggregate data to compute core metrics like market share and purchasing trends.
  • Build and maintain clean data tables and views for dashboards and recurring reports.
  • Review outputs, audit data, and ensure accuracy before presenting insights.

Skills

SQL
Python
Pandas
Data analysis
English proficiency
Attention to detail

Education

Bachelor's degree in Business Analytics, Statistics, Mathematics, Computer Science, Economics, Marketing

Tools

Snowflake
BigQuery
Redshift
Scikit-learn
statsmodels

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.
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