AI Data Scientist

Job Title: AI Data Scientist (Offshore)

Duration: 6 Months (Extendable)
Experience:  6–8 Years
Location: Offshore (Remote)
Industry: Multi-Industry (with focus on Financial Sector)
Employment Type: Contract (6 Months - Higher possiblity for extension)

Job Summary

We are seeking a highly skilled AI Data Scientist with hands-on experience in building and deploying advanced data science and machine learning models, particularly within the financial services domain . The ideal candidate will have strong proficiency in Python, SQL , and Google Cloud Platform (GCP) tools — leveraging platforms like BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, GCS, and Looker to deliver scalable and automated AI solutions.

This is an exciting 6-month contract role (with potential extension) focused on developing descriptive, predictive, and prescriptive models and deploying them in production using MLOps best practices .

Key Responsibilities

• Design and develop data science and machine learning models across descriptive, predictive, and prescriptive analytics.

• Work closely with business stakeholders—especially in the financial sector —to translate complex problems into AI-driven solutions.

• Develop and automate end-to-end ML pipelines on GCP using Vertex AI, Dataflow, Pub/Sub, and Dataproc.

• Implement MLOps frameworks for continuous integration, deployment, and monitoring of machine learning models.

• Analyze large datasets using BigQuery and other GCP-native tools for data transformation, feature engineering, and model training.

• Visualize insights and performance metrics using Looker and other BI tools.

• Collaborate with data engineers, analysts, and cloud architects to ensure seamless model deployment and scalability.

• Evaluate model performance and refine algorithms for improved accuracy and business impact.
  

Required Skills & Qualifications

• 5–8 years of professional experience in data science, AI/ML , and analytics roles.

• Proven expertise in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and SQL for data analysis and model development.

• Hands-on experience with GCP ecosystem , including:

  • BigQuery (data querying and transformation)

  • Vertex AI (model training, tuning, deployment)

  • Dataflow / Dataproc (data processing pipelines)

  • Pub/Sub (event-driven data streaming)

  • GCS (Google Cloud Storage) and Looker (visualization and reporting)

• Strong knowledge of MLOps automation and continuous deployment best practices.

• Experience developing models in financial services (risk scoring, fraud detection, customer analytics, forecasting, etc.).

• Strong understanding of statistical modeling , feature engineering , and model performance evaluation .

• Excellent problem-solving and communication skills with ability to work in multi-industry environments.
  

Preferred Qualifications

• Experience in multi-cloud or hybrid environments.

• Knowledge of CI/CD pipelines for ML (GitHub Actions, Jenkins, or Cloud Build).

• Exposure to deep learning frameworks (TensorFlow, PyTorch).

• Experience in time-series forecasting , credit modeling , or financial risk analytics .