Senior Data Scientist

Overview

AIQ is an Abu Dhabi based joint venture company between Presight and ADNOC, which focuses on developing artificial intelligence technologies. AIQ develops and commercializes AI products and applications for the energy world. It aims at providing end-to-end solutions by using its data, cloud, and talents to develop AI solutions that seek to reduce costs and generate revenue for its clients. AIQ embodies an innovative and entrepreneurial spirit that embraces challenges to push boundaries and seeks to welcome professionals to its team that share the desire to make meaningful and impactful contributions to its mission. Always on the cutting edge of technology, AIQ provides its talent all the opportunities to thrive and excel. Working at AIQ includes dealing with massive data sets, an AI infrastructure that is powered by the latest NVIDIA GPU cloud computing platform and access to limitless computing, storage, and network resources.

About the role

We are seeking a Senior Data Scientist to join our team operating in the Oil and Gas sector, specifically in upstream production modeling and optimization. You will work closely with cross-functional teams to analyze data, implement, deploy and maintain solutions, and deliver actionable recommendations to improve production management and maximize operational performance.

Responsibilities

• Develop next-generation AI-enabled software products for the oil & gas industry
• Formalize Oil & Gas problems into AI problems
• Translate business objectives into actionable analyses and insights
• Contribute to the solution design, in collaboration with other data scientists, engineers, and SMEs
• Data preparation: Extract, clean, audit and preprocess data for analysis
• Data QC: Analyze the quality of data produced and proactively develop solutions to data quality issues
• Contribute to the creation of large-scale labeled databases leveraging our annotation team
• Conduct analysis and experimentation to enhance trained Large Language Models (LLMs), such as BERT, GPT, and Transformer-based models, for comprehension and generation
• Lead the exploration, design, and implementation of LLM architectures customized for NLP tasks
• Collaborate closely with cross-functional teams comprising subject matter experts, software developers, data analysts, and product managers to integrate LLM solutions into specific software systems
• Evaluate and integrate third-party tools, libraries, and frameworks to enhance model capabilities
• Stay updated on the latest advancements in NLP, machine learning, and related fields
• Evaluate proposed AI solutions with respect to the project objectives
• Keep up to date with the latest technology trends
• Apply state-of-the-art AI techniques to improve existing solutions
• Deploy and maintain AI models in production
• Help prepare and visualize interim and final results of analyses
• Communicate ideas, plans, and results effectively via oral presentations and written reports

Qualifications

• Professional Experience: At least 4 years of experience demonstrating depth and breadth in Natural Language Processing tasks with state-of-the-art deep-learning algorithms or other AI technologies
• LLM Architecture: Good understanding of the architecture underlying large language models, such as Transformer-based models, including GPT and their variants
• Language Model Training and Fine-Tuning: Experience in training large-scale language models from scratch is a plus, as well as fine-tuning pre-trained models on domain data
• Data Preprocessing for NLP: Skills in preprocessing textual data, including tokenization, stemming, lemmatization, and handling different text encoding
• Transfer Learning and Adaptation: Proficiency in applying transfer learning techniques to adapt existing LLMs to new languages, domains, or specific business needs
• Handling Ambiguity and Context in Text: Ability to design models that effectively handle ambiguities, nuances, and context in NLP
• Data Annotation and Evaluation: Skills in designing and implementing data annotation strategies for training LLMs and evaluating their performance using appropriate metrics
• Demonstrated experience in developing core AI algorithms in industry, industrial AI, or for real-world AI problems
• Evaluate the efficiency of LLM-based algorithms through testing methodologies
• Contribute to the development of tools, libraries, and frameworks optimized for LLM engineering
• Experience in the oil & gas exploration & production company or oil field services company is a plus

Key Skills

• Strong background in applied mathematics, algorithms, and coding
• Proficient in machine-learning and/or deep-learning
• Proficient in Python development language
• Familiarity with Graph & Vector databases
• Familiarity with state-of-the-art RLHF-based pipelines
• Familiarity with data retrieval techniques, RAG models, associative recall, and fact extraction tasks
• Experience with refining existing language models for natural language processing tasks using frameworks such as TensorFlow, PyTorch, Hugging Face Transformers
• Experience in frameworks like Langchain, llama-index, etc
• Strong understanding of NLP techniques, including text preprocessing, tokenization, named entity recognition, sentiment analysis, Named Entity Recognition (NER), etc
• Experience with advanced fine-tuning techniques like LoRA, QLoRA, and Supervised Fine-Tuning (SFT) for model adaptation and efficiency
• Hands-on with useful development tools (PyCharm, Jupyter, MLFlow, Git, Docker, etc)
• Results-driven and proactive personality

Educational Requirements

• Master’s degree or Ph.D. in Computer Science, Applied Mathematics, Statistics, or any AI-related field