A global tech client of ours is seeking a junior data scientist to support their global market insights team.
The team is focused on generating a deep understanding of customers and their consumers. The team taps into both research and internal data. It conducts primary research to uncover insights to develop a deeper understanding of consumers and advertisers and is a key partner for business growth.
This role provides a great opportunity to engage with one of the leading global companies, engage in cutting-edge challenges, and interact with stakeholders across the globe.
The position is 100% remote.
responsibilities :
Collaborate with the global market insights team to analyze research and internal data, uncovering deep insights about customers and consumers.
Develop advanced Python scripts for data analysis, machine learning modeling, and API development using relevant libraries
Apply machine learning techniques to build predictive models and solve complex business problems related to customer and consumer insights.
Leverage Google Cloud Platform (GCP) services, including BigQuery, Cloud Functions, and Kubernetes, to build and deploy scalable data science applications.
Implement and manage automated data workflows using tools like Airflow or Prefect to streamline processes and increase efficiency.
requirements-expected :
Project management: experience that involved data, research or analytics
Python: Advanced proficiency in Python for data analysis, scripting and API development. This includes experience with relevant libraries (e.g., pandas, scikit-learn, Flask/Django) and best practices for building scalable and maintainable APIs.
Automation: Advanced expertise in automating data workflows using Airflow, Prefect or similar to streamline processes and increase efficiency
Machine Learning: Proficient in applying machine learning techniques to build predictive models and solve business problems
Google Cloud / DevOps: Proficient in leveraging Google Cloud Platform (GCP) services and DevOps practices to build and deploy scalable applications. This includes experience with services like BigQuery, Cloud Functions, and Kubernetes, and familiarity with CI/CD pipelines.
Software Engineering: Solid understanding of software engineering principles, including data structures, algorithms, design patterns, and version control (e.g., Git). Experience with testing frameworks and code review practices.
Communication: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical audiences.
