Job Title

Job Overview We are looking for an experienced Freelance Data Scientist to join a high-performing engineering team working on scalable products for global enterprise clients. This role is ideal for professionals currently working in a 100% REMOTE setup and looking to take up a long-term freelance or part-time engagement alongside their primary role with competitive compensation and meaningful additional income. Company Background We are a product engineering firm partnering with top-tier global organizations across consulting, fintech, retail, and consumer tech. Our 750+ strong engineering team delivers high-impact solutions across Product and Data Engineering, with deep expertise in Agentic AI, GenAI, RPA, and Full-stack development. Key Responsibilities Knowledge Graphs & Graph-Based Systems Design, build, and evolve enterprise knowledge graph systems , including: Ontology and schema design Entity modeling and relationship extraction Graph alignment, merging, versioning, and schema evolution Operate knowledge graphs across heterogeneous enterprise data sources at scale Enterprise Search & Retrieval Develop and operate enterprise search and information retrieval systems using hybrid approaches , combining: Semantic retrieval (embeddings, vectors) Graph traversal and reasoning Symbolic search and metadata-based retrieval Learning-to-rank for high-precision enterprise use cases Graph-Based Reasoning & Explainability Implement graph-based reasoning and memory systems to support: Multi-hop reasoning Context persistence Explainable and traceable decision paths Apply graph algorithms such as ranking, path finding, entity resolution, link prediction, and community detection to improve relevance, coverage, and inference quality LLM, RAG & Agentic AI Systems Build graph-augmented RAG pipelines integrating knowledge graphs with LLMs Develop agentic AI systems supporting planning, tool use, retrieval, grounding, and long-horizon task execution Implement MCP-based workflows and orchestration for multi-step enterprise AI use cases Machine Learning & NLP Design and scale traditional ML and NLP systems , including: Recommender systems Learning-to-rank models Topic modeling Entity resolution and classification pipelines Own ML evaluation and benchmarking , including offline metrics, error analysis, and online experimentation Collaboration & Platform Integration Work closely with data engineering and platform teams on large-scale pipelines, vector databases, feature stores, and graph databases Partner with product, security, and compliance teams to integrate AI capabilities into Simpplr’s enterprise platform Engagement Details Commitment: ~35 hours per week with predictable wokload and clear deliverables Work Model: 100% remote engagement from our side Compensation: Monthly payouts with a transparent pay cycle Tenure: Long-term engagement for high performers; continuity and stability assured Eligibility: Open only to professionals currently working in a full-time remote role (validated during screening) Growth: Opportunity to work on complex, high-impact products alongside senior engineering leadership