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Aera Technology is a Decision Intelligence company that helps enterprises transform decision-making through its Aera Decision Cloud platform. The platform integrates with existing systems to digitize, augment, and automate decisions in real time, delivering millions of recommendations that drive significant revenue gains and cost savings for global enterprises.
In this Associate Data Scientist role, you will partner with product and domain experts to translate business questions into analytical and modeling problems. You'll perform deep exploratory data analysis on complex, noisy, and incomplete datasets; validate data quality; uncover patterns; and frame hypotheses. You will design and implement features, select appropriate modeling approaches (regression, tree-based models, time series, clustering), and benchmark alternatives.
Key responsibilities include writing clean, well-structured Python code and notebooks for interactive analysis, experimentation, and result communication. You'll build end-to-end data and modeling pipelines covering data extraction, preprocessing, feature generation, model training, evaluation, and inference—ensuring they are modular, testable, and reproducible. You'll collaborate with engineering teams to productionize models on the Aera platform, including packaging, versioning, monitoring, and validation. Finally, you'll communicate findings and recommendations clearly to both technical and non-technical stakeholders using visualizations, written narratives, and live walkthroughs.
Aera Technology was founded in 2017 and is headquartered in Mountain View, California. The company is a Series D start-up with teams across Mountain View, San Francisco, Bucharest, Cluj-Napoca, Paris, Munich, London, Pune, and Sydney. The company offers competitive salary, stock options, comprehensive medical insurance, term insurance, accidental insurance, paid time off, maternity leave, unlimited access to online professional courses, flexible working environment, and office perks.
REQUIREMENTS:
- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field
- 1–3 years of experience in data science, data analysis, or ML engineering, or equivalent strong project/internship experience
- Strong proficiency in Python for data analysis: pandas, NumPy, and common scientific/ML libraries (scikit-learn; TensorFlow/PyTorch familiarity is a plus)
- Solid experience with exploratory data analysis and statistical analysis; comfortable working in notebooks to iteratively explore data and build intuition
- Good working knowledge of SQL and data manipulation; able to join, aggregate, and transform data from multiple sources
- Experience structuring code into reusable components and applying basic software engineering practices (version control, testing, documentation)
- Strong analytical thinking and problem-solving skills with a bias for clear, data-backed decision making
NICE TO HAVE:
- Exposure to production ML/analytics systems (scheduling, APIs, CI/CD, monitoring)
- Experience with cloud platforms (AWS, GCP, or Azure) and distributed data frameworks (e.g., Spark)
- Domain experience in supply chain, logistics, or operations
