Senior Ml Data Analyst (Remote) | Power Bi & Sql Expert

Fullstack; Quilmes; A distancia; ARS 1.200.000 - 1.800.000; Jornada completa

Descripción de la vacante

Fullstack is seeking a Machine Learning Engineer specializing in Python and NLP for finance domain applications. You will build document understanding models, deploy REST APIs, and design data pipelines to support reconciliation workflows.

Ideal candidates have 2–5 years in ML engineering, strong Python skills (Pandas, NumPy, scikit-learn), and hands-on NLP with spaCy, NLTK, or transformers. Familiarity with Azure ML and Docker is a plus.

Formación

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

Responsabilidades

• Develop and implement ML models for document understanding and processing.
• Utilize Python libraries for data manipulation and analysis.
• Apply NLP techniques using spaCy, NLTK, or transformers.
• Implement fuzzy matching algorithms for data accuracy.
• Process documents using OCR, PDF parsing, and Excel data extraction methods.
• Deploy ML 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.

Conocimientos

Python

Pandas

NumPy

scikit-learn

spaCy

NLTK

Transformers

Fuzzy matching

OCR

PDF parsing

Excel extraction

REST APIs

Docker

Azure ML

TensorFlow

PyTorch

LLMs

Azure Cognitive Services

Finance domain

NLP

Educación

Master’s degree in Computer Science/Data Science

Herramientas

Docker

Azure ML

Azure Cognitive Services

Descripción del empleo

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.