Collect, preprocess, and analyze large datasets from various sources to extract actionable insights and identify patterns, trends, and relationships.
Develop, implement, and validate machine learning and statistical models to improve the accuracy and effectiveness of our product recommendation platform.
Collaborate with cross-functional teams, including developers, AI researchers, and UI/UX designers, to understand their data needs and provide appropriate solutions.
Design and execute experiments to test hypotheses, validate models, and assess the impact of new features and improvements.
Monitor and evaluate the performance of existing models, identifying areas for enhancement and optimization.
Communicate findings and insights to both technical and non-technical stakeholders through clear, concise reports and visualizations.
Stay up-to-date with the latest developments in data science, machine learning, and related technologies, bringing new ideas and approaches to the team to drive innovation.
Requirements:
Core Programming and Frameworks :
Proficiency in Python for data analysis, scripting, and automation.
Experience with FastAPI for developing and consuming APIs.
Familiarity with Argo Workflows for orchestrating data pipelines.
Data Engineering :
Strong understanding of DBT for data transformation and modeling
Proficiency in SQL for querying and managing relational databases
Experience with cloud-based data warehouses (e.g., BigQuery, Snowflake, or Redshift).
Knowledge of market segmentation and consumer behavior analysis.
Familiarity with tools for sentiment analysis and competitive analysis.
Experience collecting data from external APIs and web scraping.
Nice to have :
Familiarity with Google Cloud Platform (GCP) services, such as BigQuery, Dataform, and Vertex AI.
Experience with DBT for data pipeline development and management
Knowledge of additional programming languages, frameworks, or tools relevant to the tech stack such as FastAPI, Pedantic, TypeScript.
7 397 - 8 877 USD
Net/month - B2B
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