Society of Exploration Geophysicists
Senior Data Scientist
Society of Exploration Geophysicists, San Antonio, Texas, United States, 78208
Position SummaryWe are seeking a highly skilled and experienced Senior Data Scientist with a specialization in AI/ML Engineering to join our dynamic Data Science and AI team. In this role, you will be instrumental in transforming data into actionable insights and innovative solutions that drive our business strategy forward. You will leverage advanced machine learning, deep learning, and neural network techniques to solve complex business challenges, collaborating closely with cross-functional teams to design, develop, and deploy scalable AI-driven models and algorithms. This position offers the opportunity to be at the forefront of AI/ML advancements, applying your expertise to real-world industrial analytics.Key ResponsibilitiesSolution Development:
Engage in the ideation, prototyping, and implementation of new AI/ML solutions to meet emerging business requirements.Machine Learning Pipelines:
Design, develop, and implement end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.Deep Learning Models:
Develop, train, and optimize deep learning models using neural network architectures (e.g., CNNs, RNNs, Transformers, GANs) and frameworks such as TensorFlow, Keras, or PyTorch. Apply these models to solve complex problems in areas like computer vision, natural language processing (NLP), and time-series forecasting.Collaboration:
Work closely with data architects, data engineers, and software developers to ensure effective data collection, processing, and storage. Collaborate with external partners, research institutions, and subject matter experts to gather domain-specific knowledge and datasets.Exploratory Data Analysis:
Perform exploratory data analysis to identify patterns, generate insights, and communicate findings to stakeholders.Model Optimization:
Optimize model performance by addressing issues such as overfitting, underfitting, and bias, ensuring scalability and performance in production environments.Mentorship:
Mentor junior data scientists in model development, data handling, and ethical considerations in AI/ML practices.Continuous Learning:
Stay abreast of the latest advancements in machine learning and AI research, applying new methods to enhance model performance and scalability.Desired Skills and ExperienceEducation:
Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related field with 5+ years of relevant experience.Technical Proficiency:
Expertise in Python and proficiency in machine learning frameworks (TensorFlow, PyTorch, scikit-learn). Experience with cloud platforms such as Azure, AWS, or Google Cloud for deploying big data and ML solutions.Deep Learning Expertise:
Extensive hands-on experience in applying deep learning techniques and neural networks to real-world problems, particularly in industrial analytics. Proven ability to develop, train, and optimize models for high-impact applications such as image recognition, NLP, and multimodal modeling.Analytical Skills:
Strong problem-solving, critical thinking, and analytical capabilities. Experience with both relational and non-relational databases, time-series data, and data visualization techniques.Communication:
Excellent verbal and written communication skills with the ability to convey complex technical concepts to non-technical stakeholders clearly and effectively.Collaboration:
A strong team player mindset capable of working collaboratively within diverse teams and contributing to an inclusive work environment.Continuous Learning:
A pronounced passion for continuous learning and staying ahead in AI/ML fields, with enthusiasm for applying new technologies to solve real-world problems.Why Join Us:Join our cutting-edge Data Science & AI team and contribute to the future of AI/ML technology! In this role, you'll leverage Azure to drive innovation and operational excellence in our AI/ML initiatives.Here's what you can expect:Be at the forefront of AI/ML advancements, applying your skills to solve real-world problems.Collaborate with a talented team of Data Scientists, ML Engineers, and cloud experts.Work in a fast-paced environment that fosters continuous learning and growth.Make a significant impact on the company's success through the power of AI/ML.
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Engage in the ideation, prototyping, and implementation of new AI/ML solutions to meet emerging business requirements.Machine Learning Pipelines:
Design, develop, and implement end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.Deep Learning Models:
Develop, train, and optimize deep learning models using neural network architectures (e.g., CNNs, RNNs, Transformers, GANs) and frameworks such as TensorFlow, Keras, or PyTorch. Apply these models to solve complex problems in areas like computer vision, natural language processing (NLP), and time-series forecasting.Collaboration:
Work closely with data architects, data engineers, and software developers to ensure effective data collection, processing, and storage. Collaborate with external partners, research institutions, and subject matter experts to gather domain-specific knowledge and datasets.Exploratory Data Analysis:
Perform exploratory data analysis to identify patterns, generate insights, and communicate findings to stakeholders.Model Optimization:
Optimize model performance by addressing issues such as overfitting, underfitting, and bias, ensuring scalability and performance in production environments.Mentorship:
Mentor junior data scientists in model development, data handling, and ethical considerations in AI/ML practices.Continuous Learning:
Stay abreast of the latest advancements in machine learning and AI research, applying new methods to enhance model performance and scalability.Desired Skills and ExperienceEducation:
Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related field with 5+ years of relevant experience.Technical Proficiency:
Expertise in Python and proficiency in machine learning frameworks (TensorFlow, PyTorch, scikit-learn). Experience with cloud platforms such as Azure, AWS, or Google Cloud for deploying big data and ML solutions.Deep Learning Expertise:
Extensive hands-on experience in applying deep learning techniques and neural networks to real-world problems, particularly in industrial analytics. Proven ability to develop, train, and optimize models for high-impact applications such as image recognition, NLP, and multimodal modeling.Analytical Skills:
Strong problem-solving, critical thinking, and analytical capabilities. Experience with both relational and non-relational databases, time-series data, and data visualization techniques.Communication:
Excellent verbal and written communication skills with the ability to convey complex technical concepts to non-technical stakeholders clearly and effectively.Collaboration:
A strong team player mindset capable of working collaboratively within diverse teams and contributing to an inclusive work environment.Continuous Learning:
A pronounced passion for continuous learning and staying ahead in AI/ML fields, with enthusiasm for applying new technologies to solve real-world problems.Why Join Us:Join our cutting-edge Data Science & AI team and contribute to the future of AI/ML technology! In this role, you'll leverage Azure to drive innovation and operational excellence in our AI/ML initiatives.Here's what you can expect:Be at the forefront of AI/ML advancements, applying your skills to solve real-world problems.Collaborate with a talented team of Data Scientists, ML Engineers, and cloud experts.Work in a fast-paced environment that fosters continuous learning and growth.Make a significant impact on the company's success through the power of AI/ML.
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