Data Scientist

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Data Scientist with Bachelor’s Degree in Computer Science, Computer Information Systems, Information Technology, or a combination of education and experience equating to the U.S. equivalent of a Bachelor’s degree in one of the aforementioned subjects.

• Analyze large-scale structured and semi-structured datasets to uncover patterns, trends, and insights that support business and product decisions.
• Develop, train, and evaluate machine learning models for use cases such as prediction, classification, anomaly detection, and forecasting.
• Perform exploratory data analysis (EDA) to understand data distributions, detect anomalies, and guide feature engineering strategies.
• Apply statistical techniques including hypothesis testing, regression analysis, and probability modeling to validate results and support decision‑making.
• Design and implement feature engineering pipelines to transform raw data into meaningful inputs for machine learning models.
• Build and compare multiple models using appropriate evaluation metrics (accuracy, precision, recall, F1-score, ROC‑AUC) and optimize performance through tuning.
• Work with large datasets using distributed computing frameworks or cloud‑based platforms to ensure scalability and efficiency.
• Develop data visualizations, dashboards, and reports to effectively communicate analytical findings to technical and non‑technical stakeholders.
• Collaborate with cross‑functional teams including product managers, engineers, and business teams to translate business problems into data‑driven solutions.
• Support the deployment of machine learning models into production by working with engineering teams and ensuring models meet performance and reliability standards.
• Monitor model performance over time and assist in updating models based on new data and changing business requirements.
• Write clean, modular, and maintainable code following best practices in software development and version control.
• Document analytical workflows, model assumptions, and results to ensure reproducibility and knowledge sharing across teams.
• Database management: Mongo
  
  DB, SQL (Relational Databases)
• Machine learning: Tensor Flow, PyTorch, Scikit-learn, Num Py, Pandas; exposure to Spa Cy, NLTK, Hugging Face, Gensim, OpenCV
• Programming
  
  Languages:
  
  Python, SQL
• Data Visualization: Matplotlib, Seaborn, Plotly
• Development Tools: Jupyter Notebook / Jupyter Lab
• Dev Ops Tools: Git, Bitbucket

Work location is Portland, ME with required travel to client locations throughout USA.

Rite Pros is an equal opportunity employer (EOE).