Data Science Sênior

BrazilRemoteFull-timemid

Data ScienceData & AI

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Requirements Summary

Professional experience using Python for data manipulation, automation, and analytical solution development. Strong knowledge of SQL for extracting and transforming data from relational databases.

Technical Tools

Data ScienceData & AI

This senior role focuses on turning complex data into predictive models, analytical solutions, and measurable business impact.
You will develop machine learning and statistical models to address challenging business problems and support data-driven decision-making.
The position combines data exploration, SQL, Python, advanced analytics, machine learning, deep learning, and modern AI technologies.
You will also work with NLP, Generative AI, LLMs, and RAG to develop innovative analytical and intelligent solutions.
Acting as a bridge between business and technology teams, you will translate technical findings into actionable insights.
You will communicate results clearly to non-technical stakeholders and help connect analytical outcomes to strategic business objectives.
This is a fully remote opportunity for an experienced data scientist who enjoys solving complex problems through data, experimentation, and emerging AI technologies.

Develop predictive models and machine learning algorithms to solve complex business challenges and generate measurable impact.
Explore, analyze, validate, and interpret data to identify relevant patterns, insights, and opportunities.
Extract, transform, and prepare data from relational databases using SQL.
Develop analytical solutions, automations, and data manipulation processes using Python.
Apply statistical modeling and machine learning techniques to business and data analysis.
Use machine learning, deep learning, and data visualization libraries and frameworks to build analytical solutions.
Develop solutions involving Natural Language Processing, Generative AI, LLMs, and Retrieval-Augmented Generation (RAG).
Act as an interface between business and technology teams, translating business needs into analytical solutions.
Present analytical results, findings, and recommendations clearly to non-technical audiences.
Support data-driven decision-making by connecting analytical insights with business objectives.

Requirements

~1 min read

Professional experience using Python for data manipulation, automation, and analytical solution development.
Strong knowledge of SQL for extracting and transforming data from relational databases.
Knowledge of statistical modeling and machine learning techniques.
Experience with Scikit-learn, Streamlit, and Matplotlib/Pyplot.
Knowledge of TensorFlow and PyTorch.
Knowledge of NLP, Generative AI, LLMs, and Retrieval-Augmented Generation (RAG).
Experience with cloud computing environments, particularly AWS and Azure.
Experience working with notebooks and data science platforms such as Jupyter and Databricks.
Experience with experimentation and machine learning lifecycle tools such as MLflow.
Knowledge of statistical libraries including Statsmodels and SciPy.
Experience applying supervised, unsupervised, and deep learning techniques.
Strong communication skills for collaborating with both technical and business stakeholders.
Ability to present technical results and analytical insights clearly to non-technical audiences.
Experience with LangChain is desirable.
Experience with LangGraph is desirable.
Experience building chatbots is desirable.