Data Scientist

We are looking for a versatile and experienced Machine Learning Engineer to support our data engineering and analytics initiatives on Google Cloud Platform (GCP). The ideal candidate will bring expertise in unsupervised machine learning, experimentation, generative AI, and data visualization, and will help build scalable solutions that uncover insights and drive business decisions.

While experience with unsupervised learning (e.g., clustering, anomaly detection, dimensionality reduction) is highly preferred, we welcome candidates with a broader ML background who are passionate about solving complex data problems and visualizing results effectively.

Key Responsibilities:

• Design and implement unsupervised ML models to extract insights from structured and unstructured data
• Develop generative AI solutions for data augmentation, summarization, and visual storytelling
• Create interactive and compelling visualizations using traditional and GenAI tools
• Collaborate with full-stack development and platform engineering teams to integrate ML models into production systems
• Build scalable ML pipelines using GCP-native services such as BigQuery, Vertex AI, Dataflow, and Cloud Functions
• Ensure model performance, reliability, and maintainability through iterative experimentation and optimization
• Document methodologies and present findings to both technical and non-technical stakeholders

Required Qualifications:

• Strong experience with unsupervised machine learning techniques and algorithms
• Hands-on experience with GCP services including BigQuery, Vertex AI, Cloud Storage, and Dataflow
• Experience collaborating with full-stack teams to integrate ML solutions via APIs or microservices
• Proficiency in Python (including libraries like scikit-learn, TensorFlow, PyTorch) and SQL
• Experience with data visualization tools (e.g., Looker Studio, Plotly, Tableau) and GenAI platforms
• Solid understanding of statistics, feature engineering, and data preprocessing
• Ability to communicate complex findings through visual storytelling and presentations
• Familiarity with MLOps practices and model deployment in cloud environments

Preferred Qualifications:

• Knowledge of self-supervised learning or graph-based ML approaches
• Experience using GenAI frameworks and platforms such as:
• Vertex AI GenAI Studio for prompt engineering and model tuning
• OpenAI API for text generation, summarization, and embeddings
• Hugging Face Transformers for custom model deployment and fine-tuning
• LangChain, LlamaIndex, or similar frameworks for GenAI-powered applications
• RunwayML, Stability AI, or DALL·E for generative visualizations
• Prior experience in a consulting or contractor role
• GCP certification (e.g., Professional Machine Learning Engineer or Data Engineer)

Design and develop data models and analytical solutions, Optimize data analysis processes and methodologies, Ensure data solutions meet business and technical requirements, Provide technical support for data science projects, Collaborate with stakeholders to address data science needs.

Bachelor's/Master's in Engineering 2-5 years