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.

Position Summary:

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.

Required Education, Experience, and

Qualifications:

• 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.

Preferred

Skills:

• Knowledge of NLP and CV applications, including…