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Senior Data Scientist, Google Cloud Platform (GCP)

Senior Data Scientist, Google Cloud Platform (GCP)

UPS Supply Chain Solutions (UPS SCS)

5 - 10 years

17 - 22 Lacs

chennai

Posted:1 week ago| Platform:

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Skills Required

data scientist time series analysis python google cloud platform data engineer forecasting ai data warehousing advocate machine learning cloud platform sql cloud data science gcp regression clustering big data aws finance azure

Work Mode

Work from Office

Job Type

Full Time

Job Description

About The Role :
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 LeadershipLead 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 BigQuery, 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 BigQuery 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:

ProgrammingExpert-level proficiency in Python and SQL. Experience with PySpark or other big data frameworks is a plus.

GCP ServicesDeep, practical experience with core GCP data and ML services, including

Data ProcessingBigQuery, Dataflow, Cloud Composer

ML PlatformVertex AI (including Training, Prediction, and MLOps features)

StorageCloud Storage

Machine LearningExpertise in a wide range of ML techniques and algorithms, including regression, classification, clustering, and time series analysis.

ExperimentationProficiency in experimental design and analysis, such as A/B testing.

VisualizationExperience 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),

Prompt Engineering ability to design, optimize, and evaluate prompts for domain-specific use cases, familiarity with techniques like few-shot learning, chain-of-thought prompting, tool augmentation, and agent-based orchestration.

RAG & Data Integration :Hands-on experience with embeddings, vector databases (FAISS, Pinecone, Chroma DB, Vertex AI Vector Search), retrieval-augmented generation (RAG), and integrating enterprise data sources into GenAI systems

Soft
Skills:

Strong analytical and problem-solving skills, with the ability to tackle complex, ambiguous business problems.

Excellent communication and presentation skills, with the ability to tell a compelling story with data.

A collaborative mindset and the ability to influence others to align on resources and strategy.

Nice-to-Have

Google Cloud Professional Data Engineer or Machine Learning Engineer certification.

Experience with other cloud platforms (e.g., AWS, Azure).

Experience in a specific industry, such as retail, advertising, or finance.

Familiarity with generative AI technologies.

Employee Type:
Permanent

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Senior Data Scientist, Google Cloud Platform (GCP)