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Impac Exploration Services

Data Science AIML Engineer

Impac Exploration Services, Houston, Texas, United States, 77246

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Job Description Job Description

Job Description:

As an integral part of our organization, you will contribute to the development and implementation of cutting-edge machine learning and artificial intelligence solutions. You will collaborate with cross-functional teams across our organization to solve complex problems and drive innovation.

Responsibilities:

Conduct exploratory data analysis to uncover insights and trends

Develop and implement machine learning models using Python and relevant libraries

Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions

Participate in the deployment of models into production environments

Stay up-to-date with the latest advancements in data science and machine learning

Properly document code, track and monitor experiments, and build necessary repositories

Qualifications:

Pursuing a Master's or PhD degree in Computer Science, Statistics, Mathematics, or a related field. In lieu of a degree, a proven track record of innovative projects or research in the field of ML/AI

Strong foundation in data structures, algorithms, and statistics

Proficiency in Python programming and data analysis libraries

Experience with machine learning frameworks and libraries

Excellent problem-solving and analytical skills

Strong communication and interpersonal skills

At this time we are not sponsoring visas or participating in CPT programs

Preferred Qualifications:

Familiarity with cloud platforms (AWS, GCP, Azure)

Experience with big data technologies (Hadoop, Spark)

Understanding of good CI/CD workflows and processes

Knowledge of the geosciences, energy, or oil and gas industries

Benefits:

Opportunity to work on real-world projects with a significant impact

Encouraged to take advantage of opportunities for professional development, networking, authoring abstracts and research papers, and engagement with the broader data science community