Freelance Data Scientist

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