Senior Data Scientist

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August 30

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Aptus Data Labs

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Artificial Intelligence • SaaS • B2B

Aptus Data Labs is a data engineering and enterprise AI company that builds scalable AI platforms, generative intelligence solutions, and data modernization services for large organizations. The company delivers industry-focused AI and analytics products (including aptplan, aptGenAI and other platforms) and services—covering advisory, cloud migration, MLOps/LLMOps, AI governance, and on-demand talent—to help pharmaceutical, banking, manufacturing, retail and other enterprises accelerate decision-making, compliance, and operational efficiency. Aptus partners with cloud and AI providers, offers pre-built accelerators and IP, and focuses on B2B deployments and enterprise-scale SaaS solutions.

201 - 500 employees

Founded 2014

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

📋 Description

• Design, develop, and deploy end-to-end machine learning and AI models for diverse business use cases. • Apply advanced deep learning architectures (CNNs, RNNs, Transformers, etc.) for solving complex problems in vision, text, and structured/unstructured data. • Develop and fine-tune NLP models for text classification, sentiment analysis, information extraction, conversational AI, and semantic search. • Explore and implement Generative AI (LLMs, diffusion models, prompt engineering, fine-tuning, RAG pipelines, etc.) to enhance existing AI/ML capabilities. • Collaborate with product, engineering, and business stakeholders to translate requirements into AI-driven solutions. • Drive model performance optimization (scalability, latency, explainability, accuracy). • Lead and mentor junior data scientists, providing technical guidance and best practices. • Stay up to date with emerging AI/ML and GenAI frameworks, tools, and research trends.

🎯 Requirements

• Having 6+ years of experience in Data Science, AI/ML, and related fields. • Strong proficiency in Python, R, or similar languages with expertise in data science libraries (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, Hugging Face). • Proven experience in designing and deploying ML/DL models in production. • Deep knowledge of NLP techniques: embeddings, Transformers, BERT/GPT-style models, seq2seq, text generation, entity recognition. • Hands-on exposure to Generative AI (e.g., OpenAI, Hugging Face, LangChain, vector databases, RAG, LLM fine-tuning). • Strong knowledge of cloud platforms (AWS, Azure, GCP) for ML/AI model deployment. • Solid understanding of MLOps practices (model versioning, monitoring, CI/CD pipelines). • Strong analytical, problem-solving, and communication skills. • Ability to work in a fast-paced, collaborative environment.

🏖️ Benefits

• This is a remote position.