We are seeking an experienced Data Scientist with strong hands-on expertise in predictive modeling, machine learning, AutoML, and cloud data environments. This role involves designing custom models, leveraging enterprise cloud platforms, and delivering scalable data solutions that support strategic business initiatives.

Experience Required:

2 years minimum in a data science role (7–10 years preferred)

Key Responsibilities:

Apply data analysis, statistics, and machine learning techniques to deliver business insights and support decision-making
Leverage AutoML tools and build custom solutions to address business problems
Develop, optimize, and maintain analytics pipelines with large and complex datasets
Execute supervised and unsupervised machine learning models, including deep learning and reinforcement learning where appropriate
Perform model tuning through hyperparameter optimization and implement performance improvements
Collaborate with data engineering and business stakeholders to translate requirements into deliverables
Utilize cloud platforms and SQL for scalable model development and deployment

Must-Have Skills:

Minimum 2 years of experience as a Data Scientist (7–10 years preferred)
Proficiency in Python, PySpark, and/or R
Strong understanding and application of machine learning algorithms:
Unsupervised (clustering, dimensionality reduction, recommendation systems, graph algorithms)
Supervised (classification, regression, decision trees, ensemble methods)
Deep learning (CNN, GNN, RNN) and reinforcement learning
Experience building and managing data science workflows across the full lifecycle (exploration to production)
Solid SQL knowledge; hands-on experience with Google BigQuery preferred (BigQuery ML, BigQuery Studio)
Experience with cloud platforms at an enterprise scale (GCP preferred; AWS or Azure acceptable)

Nice-to-Have: