Backend Engineer/Data Scientist (Ml/Ai) & Data Engineering

Dear All,

We are hiring for Cloud Native Engineering – DevOps for one for our product-based organisation based out in Houston USA.

:

Experience: 5-15 years

Location: Houston USA

On a Normal Day, You Will

• As a Data Scientist/Data Engineer primary responsibilities will include data pre-processing, algorithm development, and predictive modelling to optimize operations and decision-making processes. Proficiency in programming languages such as R and Python, as well as good experience with SQL and NoSQL databases, is essential for this role.
• Additionally, domain knowledge in the Oil and Gas industry is crucial to understanding the specific challenges and requirements of the sector.

You Have to have the below

Key Responsibilities:

Data Analysis and Modeling:

• Apply statistical analysis, data mining, and machine learning techniques to discover patterns, correlations, and anomalies in large and complex datasets.
• Identify, gather, and preprocess relevant data from various sources, such as sensors, equipment logs, production databases, and external datasets.
• Develop and implement predictive models to optimize production processes, forecast equipment failures, predict demand, and allocate resources effectively.

Algorithm Development and Deployment:

• Utilize programming languages such as R and Python to build scalable and efficient algorithms.
• Design and develop algorithms and models to address specific business challenges in the Oil and Gas sector, including reservoir characterization, drilling optimization, pipeline integrity, or refinery process optimization.
• Collaborate with software engineers and data engineers to deploy models and algorithms in production environments, ensuring reliability, scalability, and efficiency.

Database Management:

• Design and optimize database structures to store and retrieve large volumes of structured and unstructured data.
• Develop and maintain data pipelines to ensure the seamless flow of data between different systems and databases.
• Utilize SQL and NoSQL databases to extract, manipulate, and analyze data effectively.

Data Visualization and Reporting:

• Create visually compelling dashboards, reports, and interactive visualizations to communicate complex data-driven insights to stakeholders, enabling informed decision-making.
• Utilize visualization tools such as Tableau, Power BI, or matplotlib to present findings, trends, and recommendations to technical and non-technical audiences.

Cross-functional Collaboration:

• Collaborate with domain experts, engineers, and subject matter experts across different departments to understand business requirements and develop data-driven solutions.
• Work closely with geoscientists, reservoir engineers, production engineers, and other stakeholders to integrate data science techniques into existing workflows and processes.

Research and Innovation:

• Stay updated with the latest advancements in data science, machine learning, and AI technologies relevant to the Oil and Gas sector.
• Identify opportunities for innovation and propose new methodologies, techniques, or tools to enhance operational efficiency, safety, and sustainability.

Qualifications and Skills:

• Knowledge of big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure) is a plus.
• Proficiency in programming languages such as R and Python for data analysis and model development.
• Familiarity with data visualization tools such as Tableau, Power BI, or matplotlib.
• Experience with SQL and NoSQL databases for data manipulation and management.
• Excellent problem-solving skills, critical thinking abilities, and attention to detail.
• Strong knowledge of the Oil and Gas sector, including exploration, production, refining, and distribution processes.
• Expertise in statistical analysis, predictive modeling, and machine learning algorithms.
• Strong communication and presentation skills, with the ability to explain complex concepts to technical and non-technical stakeholders.
• Proven experience as a Data Scientist, preferably within the Oil and Gas industry.
• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.