Our client is seeking an experienced Senior Data Scientist with AI expertise who has a strong background in Neo4j and Python. This role requires a deep understanding of graph databases, AI/ML algorithms, and data engineering while also playing a key role in pre-sales discussions to help drive business growth.

Responsibilities:

AI & Data Science

• Design, develop, and deploy AI/ML models leveraging Python and Neo4j (Graph Data Science Library).
• Apply advanced machine learning techniques to solve complex business problems.
• Work with graph-based machine learning for fraud detection, recommendation systems, and knowledge graphs.
• Optimize and fine-tune AI/ML models for scalability and performance.
• Graph Database & Big Data
• Build and maintain graph-based data models using Neo4j to analyze relationships and insights.
• Utilize Cypher query language to manipulate and extract insights from graph databases.
• Work with large-scale datasets and integrate Neo4j with cloud-based data pipelines.
• Presales & Client Engagement
• Partner with the sales and business development teams to present AI/ML solutions to clients.
• Lead technical discussions, proof of concepts (PoCs), and demos for potential clients.
• Translate business challenges into AI-driven solutions and provide strategic recommendations.
• Prepare technical proposals, solution architecture, and documentation to support pre-sales activities.

Cloud & MLOps

• Deploy AI/ML models in cloud environments (AWS, Azure, or GCP).
• Utilize Kubernetes, Docker, and MLOps tools (MLflow, Kubeflow) for scalable deployments.
• Work with CI/CD pipelines for continuous integration and deployment of machine learning solutions.

Requirements:

• Experience Range: 8+ Years 
• Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field.
• Proven experience in ETL testing, data validation, and quality assurance.
• Strong understanding of ETL concepts, data warehousing, and database management.
• Proficiency in SQL and experience with ETL tools (e.g., Informatica, Talend, Apache Nifi).
• Familiarity with automated testing tools and frameworks is a plus.
• Excellent analytical and problem-solving skills.
• Strong communication and interpersonal skills, with the ability to work collaboratively in a team environment.
• Detail-oriented with a strong focus on data quality and accuracy.