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Company Overview: -
- Mid-Sized Pioneering IT and Engineering Services Company
- Domains: Hi-Tech, Automotive, Manufacturing, Telecom, Medical and Life Sciences, Pharmaceutical
- Successfully service Fortune 500 Companies
- Customer Geographies: North America, Europe, Japan, Korea, China
Job Description – Senior Data Scientist
ABOUT THE ROLE
We are looking for an accomplished Senior Data Scientist for the design, development, & deployment of cutting-edge ML and AI solutions. In this leadership role, you will drive technical strategy, mentor a team of data scientists, and collaborate with cross-functional stakeholders to deliver impactful, production-ready AI systems. You will serve as technical authority on NLP, LLMs, & deep learning, translating complex business problems into scalable solutions.
KEY RESPONSIBILITIES
- Design, develop, and implement machine learning models to deliver personalized content.
- Build and maintain scalable data pipelines to ingest data/metadata/signals from websites, structured and unstructured content sources.
- Consolidate user data from multiple channels into unified user profiles.
- Design and implement feature engineering pipelines, engagement feature computation, content feature extraction, embeddings, and reusable feature definitions.
- Develop candidate generation solutions using vector embeddings, hybrid retrieval techniques, and ANN search.
- Build, evaluate, and optimize ML models using contextual features, including reranking and rank techniques.
- Develop and maintain APIs for integration with multiple applications and digital platforms.
- Train, validate, deploy, and monitor machine learning models using established MLOps practices, model registries, and automated deployment pipelines.
- Implement scalable vector database solutions to support semantic search and embedding-based retrieval.
- Develop ML Models using metadata, taxonomy, and content-based features.
- Monitor model performance, recommendation quality, feature quality, and data drift, and recommend improvements to maintain model effectiveness.
- Support A/B testing, experimentation, and continuous optimization by analyzing user feedback.
- Collaborate with data engineers, software engineers, product managers, and business stakeholders to deliver production-ready AI and machine learning solutions.
- Ensure compliance with data governance, privacy, security, & organization standards in data science workflows.
- Contribute to CI/CD pipelines, infrastructure automation, technical documentation, engineering best practices.
- Mentor junior team members through technical guidance, code reviews, and knowledge sharing.
REQUIRED QUALIFICATIONS
- 6–10 years of experience in Data Science, Machine Learning, Artificial Intelligence.
- Strong experience building and deploying machine learning models for predictive analytics.
- Hands-on expertise in feature engineering, user profiling, behavioral analytics.
- Experience implementing embeddings, semantic search, and ANN/CNN/RNN retrieval techniques.
- Strong Python skills with experience using ML frameworks like Scikit-learn, TensorFlow, or PyTorch.
- Experience with distributed data processing frameworks such as Apache Spark or Databricks.
- Strong SQL skills and experience working with large-scale structured and unstructured datasets.
- Experience with vector databases and modern data storage technologies.
- Knowledge of MLOps, model deployment, experiment tracking, model versioning, monitoring.
- Experience working with cloud platforms such as Microsoft Azure, AWS, or Databricks.
- Understanding of REST APIs, scalable inference services, and cloud-native application architectures.
- Experience working with Knowledge Graphs, enterprise taxonomies, and ontology-based data models for semantic search.
- Hands-on experience with graph databases (e.g., Neo4j, Amazon Neptune, TigerGraph) and graph query languages such as Cypher or SPARQL.
- Understanding of graph analytics, including graph traversal, similarity analysis, node embeddings, and relationship-based feature engineering for ML models.
- Familiarity with semantic web standards such as RDF, OWL, SKOS, and metadata modeling concepts to support knowledge representation and content enrichment.
- Experience leveraging knowledge graphs, taxonomies, and vector embeddings to enhance semantic retrieval, and Retrieval-Augmented Generation (RAG) solutions.
- Strong analytical, problem-solving, communication, and collaboration skills.
PREFERRED QUALIFICATIONS
- Master's degree in Data Science, Artificial Intelligence, Machine Learning, Computer Science, or a related field.
- Experience with Generative AI, LLMs, Retrieval-Augmented Generation (RAG), and AI-assisted search.
- Familiarity with vector databases such as Pinecone, Milvus, Weaviate, or Azure AI Search.
- Experience with taxonomy management, knowledge graphs, or ontology-based systems.
- Knowledge of IaC (Terraform) & containerization technologies such as Docker and Kubernetes.
- Experience implementing A/B testing frameworks and recommendation evaluation methodologies.
- Exposure to enterprise-scale personalization platforms and cloud-native AI solutions.
- Relevant cloud platform or machine learning certifications are an added advantage.
WHAT WE OFFER
- Awesome Culture: Creative Synergies has a flat organization and an agile culture of positivity, entrepreneurial spirit, customer centricity, celebrating technical excellence, teamwork, and meritocracy
- Opportunity to work with Customers who are technology Leaders (including Global Fortune 500 Customers) & work on Real-World Problems that matter and are often mission-critical
- Leadership role with significant influence over AI strategy and team direction.
- Access to state-of-the-art GPU infrastructure and cutting-edge AI tools.
- Competitive compensation package with performance-based incentives.
- Flexible working arrangements with hybrid options.
- Continuous learning budget for conferences, courses, and certifications.
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