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Senior Data Scientist - Vaga afirmativa para mulheres cis e trans

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São Paulo

Teletrabalho

BRL 160.000 - 200.000

Tempo integral

Hoje
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Resumo da oferta

A leading data-driven consultancy in São Paulo is seeking a Data Scientist to design and deploy machine learning models. The role involves collaboration across teams to solve complex business problems using strong technical skills and mentoring abilities. Candidates should be proficient in Python and have experience with modern data technologies. Join a culture that prioritizes empathy and collaboration while making a significant impact in the data field.

Serviços

Work from home or anywhere you want
Access to gyms and wellness programs
Life, health, and dental insurance
In-person meetings 3x a year
Book a coworking space wherever you like
Opportunities for promotion during reviews

Qualificações

  • Practical experience with tools in the modern data stack.
  • Fluent in English for international collaboration.
  • Demonstrated ability to mentor and enable teams.

Responsabilidades

  • Design, develop, and deploy machine learning models.
  • Collaborate with analysts and engineering teams.
  • Monitor and troubleshoot model performance.

Conhecimentos

Strong communication
Excellent problem-solving skills
Curiosity
Collaboration
Entrepreneurship

Formação académica

Degree in Computer Science, Statistics, Engineering, Economics, or related quantitative field

Ferramentas

Python (pandas, numpy, scikit-learn, pyspark)
Google Cloud Platform (GCP)
PostgreSQL
Machine Learning models (xgboost, logistic regression)
Databricks
Descrição da oferta de emprego
Overview

Who we are

At Artefact Brasil, we believe in and live a culture based on empathy! A healthy work environment is a place where all voices are heard, respected, and valued. We are committed to building a more diverse and inclusive environment, because empathy is for everyone, regardless of ethnicity, color, gender, sexual orientation, gender identity, disability, or religious belief. We want incredible minds and hearts with us! Come and be Artefact!

What you will be doing:

Responsibilities
  • Design, develop, and deploy end-to-end machine learning models, from data acquisition and feature engineering to production monitoring.
  • Collaborate with data analysts, product managers, and engineering teams to translate business problems into data science frameworks and ensure impactful outcomes.
  • Develop and refine complex data features from large-scale datasets to improve model accuracy and business performance.
  • Champion data quality and integrity, defining the requirements for robust datasets needed for advanced analytics and modeling.
  • Monitor, analyze, and troubleshoot the performance of deployed models, addressing issues like concept drift, data quality degradation, and performance bottlenecks.
  • Provide technical leadership in the application of statistical modeling, machine learning, and advanced analytics to solve complex business problems.
  • Document and present complex methodologies, model findings, and strategic recommendations to both technical and non-technical stakeholders.
  • Lead by example, championing a culture of scientific rigor, experimentation, and continuous learning within the data science team.
  • Mentor and coach junior data scientists and analysts, fostering their growth through code reviews, design discussions, and knowledge sharing.

What we are looking for:

A degree in Computer Science, Statistics, Engineering, Economics, or a related quantitative field.

  • Strong communication and interpersonal skills, with the ability to collaborate across multiple teams and levels of the organization.
  • Demonstrated ability to balance hands-on technical delivery with mentoring and team enablement.
  • Excellent problem-solving skills, with the ability to troubleshoot complex technical issues.
  • Curiosity: You are passionate about finding innovative solutions to complex problems. You seek to understand the entire value chain and how your ML models integrate with front-end applications, back-end systems, and the underlying data infrastructure to deliver business value.
  • Collaboration: Knowledge sharing is essential to you, and you actively contribute to spreading information within Artefact.
  • Entrepreneurship: You bring solutions, new ideas, and innovations.
  • Fluent English: You are comfortable communicating in English, as it is essential for working in our international environment.

Required Technical Experience

You have practical experience with several tools and technologies in the modern data stack, such as:

  • Programming Languages: Strong skills in Python for data science (pandas, numpy, scikitlearn, pyspark); Nice to Have experience with a deep learning framework like PyTorch or TensorFlow/Keras
  • Cloud Data Platforms: Hands-on with at least one of Google Cloud Platform (GCP), AWS, Azure, Databricks
  • Data Warehousing & Databases: Familiar with tools such as PostgreSQL, SQL Server, BigQuery, Snowflake
  • Machine Learning models: Experience with supervised learning models (xgboost, logistic regression, etc), unsupervised learning models (clustering algorithms)
  • MLOPS: Experience with at least one: Databricks, mlflow, AWS Sagemaker, Vertex AI; Git code versioning workflow and platforms (Github, Azure Devops, Gitlab etc)
What we offer
  • Free Office – work from home or anywhere you want!
  • Gympass – access to gyms and wellness programs
  • Insurance – life, health, and dental coverage
  • In-person Meetings 3x a Year – our famous “Get Together” with workshops, talks, trainings, and happy hour!
  • Woba – book a coworking space wherever you like!
  • Semiannual Reviews – with opportunities for promotion

Why you should join us

  • Artefact is the place to be: come and build the future of the data field
  • Progress: every day offers new challenges and new learning opportunities
  • Culture: Empathy and Collaboration are in our DNA
  • Entrepreneurship: you will join a team of motivated entrepreneurs. We won\'t give up until we make a big difference in this industry!
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