Pune, Maharashtra, India
Social Good & Community Development
Full-Time
algoleap
Overview
Key ResponsibilitiesRequired Qualifications
- Experience: 5-7 years of professional experience as a Data Scientist or Machine Learning Engineer.
- Modeling, Analysis, & Experimentation
- Design, develop, and implement various Machine Learning (ML) models (e.g., predictive, prescriptive, clustering) to solve complex business problems across areas like demand forecasting, customer segmentation, or risk analysis.
- Conduct complex Exploratory Data Analysis (EDA) using statistical methodologies and advanced visualization techniques to uncover insights and define metrics.
- Develop and manage rigorous A/B testing frameworks and experiments to validate hypotheses and measure the impact of deployed models.
- Translate ambiguous business questions and large datasets into clear, actionable data science roadmaps and deliverables.
- Google Cloud Platform (GCP) Focus âï¸
- Design and implement end-to-end ML Pipelines using Google Cloud Vertex AI (e.g., Feature Store, Workbench, Experiments, Pipelines).
- Leverage BigQuery for massive-scale data storage, manipulation, and high-performance querying using SQL.
- Utilize core GCP data services such as Cloud Storage, Cloud Dataflow (Apache Beam), and Cloud Composer (Apache Airflow) for reliable data ingestion, transformation, and workflow orchestration.
- Ensure solutions are scalable, cost-efficient, and maintain high standards of security and governance within the GCP environment.
- Technical Stack: Expert proficiency in Python and its scientific libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
- GCP Expertise: Strong hands-on experience with key Google Cloud services, including BigQuery, Vertex AI, and Cloud Storage.
- Modeling: Proven ability to build, train, and evaluate production-grade ML models.
- SQL & Data Wrangling: Expert level SQL proficiency for large-scale data manipulation and querying.
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