Senior Data Scientist, Google Cloud Platform; GCP

Position: Senior Data Scientist, Google Cloud Platform (GCP)
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Senior Data Scientist, Google Cloud Platform (GCP)

A Senior Data Scientist with experience in Google Cloud Platform (GCP) is responsible for leading complex data science projects, building and deploying advanced machine learning (ML) models, and leveraging GCP's ecosystem to drive strategic business decisions. This role requires expert technical skills, strong business acumen, and the ability to collaborate with and mentor other team members.

Responsibilities

End-to-End Project Leadership:
Lead and manage the entire data science project lifecycle, from problem definition to model deployment and monitoring.
Advanced Analytics and Modeling:
Design, develop, and implement advanced statistical and machine learning models to solve complex business problems, such as forecasting, classification, clustering, and optimization.
Leverage expertise in advanced statistical techniques, including hypothesis testing, regression analysis, and causal inference.
GCP-Specific Responsibilities:
Architect and build scalable data pipelines and ML model workflows using GCP services such as Big Query, Dataflow, Vertex AI, and Cloud Composer.
Develop and manage data warehousing and data lake solutions on GCP, ensuring data quality, integrity, and security.
Utilize and optimize GCP's machine learning services, including Vertex AI for model training and serving, and Big Query ML.

Cross-Functional Collaboration:

Partner with product managers, data engineers, and business stakeholders to translate ambiguous business needs into tractable data science problems and impactful solutions.
Communicate complex analytical findings and model results clearly and effectively to both technical and non-technical audiences.
Mentorship and Best Practices:
Provide technical guidance and mentorship to junior data scientists and analysts.
Advocate for and establish best practices in data science, including code quality, model validation, and responsible AI principles.

Qualifications

Education:

A Master's degree or Ph.D. in a quantitative field such as Statistics, Mathematics, Data Science, Computer Science, or Engineering is often preferred.

Experience:

5+ years of experience in a data science role, with proven experience building and deploying production-level models.
Extensive, hands-on experience developing and implementing solutions on the Google Cloud Platform.
Technical

Skills:

Programming:
Expert-level proficiency in Python and SQL.

Experience with PySpark or other big data frameworks is a plus.
GCP Services:
Deep, practical experience with core GCP data and ML services, including:
Data Processing:
Big Query, Dataflow, Cloud Composer
ML Platform:
Vertex AI (including Training, Prediction, and MLOps features)
Storage:
Cloud Storage
Machine Learning:
Expertise in a wide range of ML techniques and algorithms, including regression, classification, clustering, and time series analysis.
Experimentation:
Proficiency in experimental design and analysis, such as A/B testing.
Visualization:

Experience with data visualization tools like Looker, Tableau, or similar platforms
Gen AI
LLMs :
Understand Transformer-based models (GPT, LLaMA, Mistral, etc.), fine-tuning methods (LoRA/QLoRA, RLHF),
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