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Baker Hughes

Makes oilfield equipment and gas turbines

Digital Technology Specialist - Data Science

Applied Machine LearningPosted on Nov 12
Full-timeNo salary listedIn-person

About the Job

Requirements

  • Bachelor's or master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field, with 4–6 years of experience.
  • Strong programming skills in Python and/or R.
  • Expertise in SQL and database technologies.
  • Experience with machine-learning frameworks including Scikit-learn, TensorFlow, PyTorch, and XGBoost.
  • Experience with cloud platforms including Microsoft Azure, AWS, and Google Cloud Platform.
  • Knowledge of data warehousing, data lakes, ETL/ELT pipelines, Spark, and distributed computing.
  • Familiarity with MLOps tools including MLflow, Azure ML, Databricks, Kubernetes, and Docker.
  • Experience with Generative AI, LLMs, prompt engineering, and RAG architectures.
  • Strong understanding of statistics, probability, experimental design, time-series analysis, and optimization techniques.
  • Strong problem-solving and critical-thinking abilities.
  • Excellent communication and storytelling skills.
  • Ability to work in cross-functional teams.
  • Strategic mindset focused on business outcomes.
  • Continuous learning and innovation mindset.

Responsibilities

  • Develop analytics to address customer needs and opportunities.
  • Work alongside software developers and software engineers to translate algorithms into commercially viable products and services.
  • Work in technical teams on the development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.
  • Perform exploratory and targeted data analyses using descriptive statistics and other methods.
  • Work with data engineers on data quality assessment, data cleansing, and data analytics.
  • Generate reports, annotated code, and other project artifacts to document, archive, and communicate work and outcomes.
  • Share and discuss findings with team members.
  • Analyze large structured and unstructured datasets to identify trends, patterns, and opportunities.
  • Develop statistical models to uncover insights and support business decisions.
  • Perform exploratory data analysis and hypothesis testing.
  • Create dashboards and visualizations to communicate findings.
  • Design, develop, train, and deploy machine-learning models.
  • Build predictive, classification, recommendation, and optimization solutions.
  • Apply Generative AI, LLMs, Retrieval-Augmented Generation, and Agentic AI techniques where applicable.
  • Evaluate model performance and continuously improve accuracy and reliability.
  • Build scalable data pipelines for data ingestion, transformation, and feature engineering.
  • Implement model deployment, monitoring, and lifecycle management using MLOps best practices.
  • Work with cloud-native AI and data platforms.
  • Ensure data quality, governance, security, and compliance standards.
  • Collaborate with business stakeholders to understand requirements and define success metrics.
  • Translate business problems into analytical and AI solutions.
  • Present technical findings to technical and non-technical audiences.
  • Measure and communicate the business impact of deployed solutions.
  • Stay current with advancements in AI, machine learning, generative AI, and analytics.
  • Prototype new approaches and technologies.
  • Contribute to AI strategy, governance, and responsible AI practices.

Desired Qualifications

  • Experience deploying AI solutions into production environments.
  • Knowledge of Responsible AI, AI governance, and model explainability.
  • Experience with vector databases including Pinecone, Azure AI Search, Weaviate, and Chroma.
  • Familiarity with AI agents and autonomous workflows.
  • Industry knowledge in healthcare, finance, retail, manufacturing, or telecommunications.

About the Company

Baker Hughes

Makes oilfield equipment and gas turbines

Baker Hughes makes equipment and runs field services for oil and gas producers, LNG plant operators, pipeline companies and industrial power users. Its products cover the whole gas chain, from drill bits and well completions to the compressors and turbines that chill natural gas into liquid for export. Its oilfield arm drills, completes and maintains wells, while its industrial arm designs, builds and services turbomachinery, valves and monitoring software. It earns money from equipment sales, project work and long-term service agreements that keep installed machines running. The current company formed in 2017 when Baker Hughes combined with GE's oil and gas business, and it is based in Houston.

Company size
10,001+
Company stage
IPO
Headquarters
Houston, TX
Founded
1972

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