Data Scientist — Personalization & Trading Ml (Hybrid)

Endava; Buenos Aires; Remote; ARS 139,086,000 - 200,903,000; Full time

Job summary

Endava is seeking a Machine Learning Engineer specializing in Python and NLP to join our distributed team. The role focuses on reconciliation and accounting data within the finance/fintech domain, leveraging ML models, NLP techniques, and document processing to deliver insights.

You will build data pipelines, deploy ML models as REST APIs, and collaborate with cross-functional teams to meet project goals. The ideal candidate has 2–5 years in ML engineering with NLP or financial data experience,

Qualifications

• 0–4 years of experience in Data Analysis/Analytics or similar roles; entry-level welcome with coursework or internships
• Advanced English (written and spoken)
• Foundational to intermediate SQL skills with JOINs, aggregations, and CASE WHEN
• Python scripting for data cleaning, manipulation, and processing (pandas)
• Familiarity with scikit-learn or statsmodels for predictive/modeling
• Experience cleaning/processing messy text fields
• Relational DB design and data normalization concepts
• Bachelor’s degree in Business Analytics/Statistics/CS/Economics/Marketing or related field with relevant coursework

Responsibilities

• Write, optimize, and execute SQL queries to extract data from relational databases and cloud data warehouses
• Develop, run, and validate ML models for consumer behavior and trends
• Transform raw data into core business metrics (household penetration, market share, purchasing trends)
• Build and maintain clean data tables and dashboards for stakeholders
• Review outputs for accuracy and data integrity before insights are presented
• Use conditional logic to segment data and track cohorts
• Clean, parse, and categorize unstructured or semi-structured text data
• Translate technical results into clear summaries for English-speaking stakeholders

Skills

Python (Pandas/NumPy)

NLP libraries (spaCy/NLTK/transformers

Fuzzy matching

Document processing (OCR/PDF/Excel)

ML deployment (REST APIs, Docker,Azure

Supervised/unsupervised learning

DL frameworks (TensorFlow/PyTorch)

LLMs for documents (OpenAI/Azure OpenA

Azure ML services

Education

Master’s degree in CS/DS or related field

Tools

Docker

Azure ML

Azure Cognitive Services

SQL

Job description

We are seeking a Machine Learning Engineer with strong expertise in Python and a focus on Natural Language Processing (NLP) to join our team. The ideal candidate will have experience in the finance or fintech domain, specifically in reconciliation and accounting.

Responsibilities

Develop and implement machine learning models for document understanding and processing.
Utilize Python libraries such as Pandas, NumPy, and scikit-learn for data manipulation and analysis.
Apply NLP techniques using libraries like spaCy, NLTK, or transformers.
Implement fuzzy matching algorithms (., Levenshtein distance, record linkage) for data accuracy.
Process documents using OCR, PDF parsing, and Excel data extraction methods.
Deploy machine learning models as REST APIs using Docker and Azure ML.
Understand and apply supervised and unsupervised learning techniques.
Design and manage data pipelines and ETL processes.
Collaborate with cross-functional teams to meet project goals.

Required Skills

Strong expertise in Python (Pandas, NumPy, scikit-learn).
Experience with NLP libraries (spaCy, NLTK, transformers).
Knowledge of fuzzy matching algorithms.
Document processing skills (OCR, PDF parsing, Excel extraction).
Experience in ML model deployment (REST APIs, Docker, Azure ML).
Understanding of supervised/unsupervised learning techniques.
Familiarity with deep learning frameworks (TensorFlow, PyTorch).
Experience with Large Language Models (LLMs) for document understanding (OpenAI, Azure OpenAI).
Knowledge of Azure ML services and Azure Cognitive Services.
2-5 years of experience in ML engineering, focusing on NLP or financial data processing.
Experience in the finance/fintech domain (reconciliation, accounting).

Education

Master’s degree in Computer Science, Data Science, or a related field.

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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.