Data Scientist

Company Information:  

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. 

Key Roles / Responsibilities: 

• 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 TensorFlow, 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.
• 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.
• 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 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. 

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, and other advanced deep learning models.
• Strong proficiency in programming languages like Python, R, or Julia, and hands-on experience with AI/ML frameworks (TensorFlow, 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, NoSQL) 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 experience with large-scale pre-trained models like GPT, BERT, or DALL·E.
• Expertise in model deployment and monitoring in production environments (e.g., Docker, Kubernetes, MLflow).
• Experience with version control systems (e.g., Git) and software development best practices.
• Familiarity with DevOps practices and CI/CD pipelines for machine learning projects.
• Published research in top-tier conferences or journals related to AI/ML or Generative AI. 

Working Conditions:  

• Prolonged periods sitting at a desk and working on a computer. 
• Must be able to lift 15 pounds at times. 
• Positions self to install equipment, including under desks. 
• Moves throughout the building to access files. 
• Must be able to comprehend and follow written and oral instructions.   
• Must be able to complete tasks even with frequent interruptions.   
• Must be able to use discretion and independent judgment as needed.   
• Must be able to speak clearly on the phone and to fellow workers.

This job description should not be interpreted as an exhaustive list of responsibilities or as an employment agreement between the employer and the employee. The above statements are intended to describe the general nature and level of work being performed by employees assigned to this classification and are subject to change as the needs of the employer and requirements of the job change.  Any essential functions of this position will be evaluated as necessary should an employee/applicant be unable to perform the functions or requirements due to a disability as defined by the Americans with Disabilities Act (ADA). Reasonable accommodation for the specific disability will be made for the employee/applicant when possible.