Data Science Analyst

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Aspire Software

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SaaS • Enterprise • B2B

Aspire Software is a company that focuses on acquiring and nurturing businesses with a strong foundation in outstanding products and passionate teams. As part of the Valsef Group, Aspire Software offers resources, knowledge, and a suite of best practices to enhance and expand operations for continuous improvement and sustainable growth. The company emphasizes decentralization to unlock innovation and adaptability within its acquired entities. Aspire Software is dedicated to serving its customers through long-term technology partnerships, leveraging capital and expertise in various verticals to grow both the businesses and individuals involved.

1001 - 5000 employees

☁️ SaaS

🏢 Enterprise

🤝 B2B

📋 Description

• Collaborate closely with software developers and process domain experts to turn data into actionable insights. • Analyze production and operational data, develop predictive and diagnostic models, and design processes that enhance data quality and performance across our Sigmafine platform and customer implementations. • Work alongside experienced professionals delivering advanced analytics and AI solutions to customers worldwide, both remotely and on-site. • Contribute to projects involving data cleaning, feature engineering, exploratory data analysis (EDA), and the development of machine learning models that improve decision-making and process efficiency.

🎯 Requirements

• Bachelor’s degree (or higher) in Data Science, Statistics, Computer Science, or a related field. • 2–5 years of experience in data analysis, process data modeling, or applied machine learning. • Proficiency with SQL for data manipulation and analysis. • Familiarity with model development techniques such as regression, classification, clustering, forecasting, and anomaly detection. • Experience using libraries like pandas, NumPy, scikit-learn, or TensorFlow/PyTorch. • Understanding of data pipelines, ETL workflows, and data visualization tools (e.g., Power BI, Plotly, or Matplotlib). • Strong problem-solving skills and attention to data integrity, validation, and reconciliation. • Ability to translate business needs into analytical questions and communicate findings clearly. • Working proficiency in English, both written and verbal. • Nice to Have • Experience with time-series data from process historians (e.g., OSIsoft PI, Aveva, or Honeywell PHD). • Knowledge of production accounting, energy balance, or process efficiency metrics. • Exposure to industrial AI or digital twin concepts. • Familiarity with .NET, ML.net is for sale at Atom!, and ONNX model integration is a plus. • Experience with Docker, Jupyter Notebooks, and version control (Git). • Knowledge of Spanish or Italian is a plus.