Senior Data Scientist

Linqx is an industry-leading provider of end-to-end digital solutions and analytics for the oil and gas sector, leveraging advanced data analytics to optimize engineering and operations. Its cloud-based platforms deliver AI-driven insights that enhance reservoir performance and streamline workflows. Driven by a mission of data-driven innovation, Linqx combines cutting-edge technology with oilfield expertise to deliver transformative results.

Seeking an experienced and highly skilled Data Scientist to join our dynamic team. The ideal candidate will possess a strong foundation in data science, machine learning, and data engineering, with a particular focus on developing and deploying cutting-edge generative AI models. Incumbents will work closely with cross-functional teams to drive impactful data-driven decisions and innovations across the organization. Our dynamic approach to technology offers an exciting environment for this role that’s focused on big data, machine learning, and advanced analytics.

• Design, implement, and deploy advanced machine learning models and algorithms, particularly in Generative AI (e.g., GANs, transformers, diffusion models).
• Leverage deep learning frameworks (such as Tensor Flow, PyTorch, or JAX) to build and train state-of-the-art models for natural language processing (NLP), computer vision (CV), and other generative tasks.
• Collaborate with engineering teams to ensure seamless integration of AI/ML solutions into production environments, optimizing for performance and scalability.
• Work with technology and business leaders to evolve data-driven vision, communication channels, and all supporting documentation
• Utilize advanced statistical techniques and data modeling methods to analyze large, complex datasets and provide actionable insights.
• Develop data pipelines for cleaning, processing, and transforming raw data into structured formats suitable for machine learning applications (i.e. familiarity with Lakehouse deployment/governance on Medallion architecture).
• Design, build, and maintain efficient and scalable data architectures and data storage solutions.
• Work on end-to-end machine learning workflows, including data preprocessing, feature engineering, model training, evaluation, and deployment.
• Continuously evaluate and optimize model performance and contribute to improving the overall AI/ML infrastructure and processes.
• Mentor and/or manage junior data scientists and engineers, fostering a culture of collaboration and continuous learning.
• Stay updated on the latest advancements in AI/ML research and apply innovative techniques to solve business problems.
• Document and communicate findings and solutions clearly to both technical and non-technical stakeholders.
• Participate and potentially drive data-specific technology selection activities

• Master's or PhD in Computer Science, Data Science, Engineering, or a related field, with a focus on machine learning, AI, or data engineering.
• Proven expertise in Generative AI, including experience with techniques such as GANs, VAEs, transformers, RAGs, and other advanced AI and deep learning models.
• Strong proficiency in programming languages like Python, R, or Julia, and hands-on experience with AI/ML frameworks (Tensor Flow, PyTorch, Scikit-learn, etc.).
• Extensive experience with data engineering, including data wrangling, ETL processes, data storage, and real-time data processing.
• In-depth knowledge of machine learning algorithms, deep learning, and statistical modeling techniques.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and distributed computing frameworks (e.g., Spark, Hadoop).
• Experience in designing and optimizing data architectures for both batch and real-time data flows.
• Proficient with database systems (SQL, No
  
  SQL) and data query languages.
• Strong problem-solving, analytical, and critical-thinking skills with the ability to work independently or as part of a team.
• Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.

• Knowledge of NLP and CV applications, including…