Digital Technology Specialist - Data Science
Baker Hughes Company
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Benefits offered by this job
Job summary
Baker Hughes in Mumbai, India seeks a Digital Technology Specialist - Data Science to lead analytics initiatives, translate algorithms into viable products, and collaborate with software teams on applied and predictive analytics.
You will develop ML models, build scalable data pipelines, and deploy MLOps practices while ensuring data quality, governance, and security. Strong Python/R, SQL, cloud experience, and a strategic mindset are expected.
Qualifications
- Bachelor's or master's degree in data science, CS, statistics, mathematics, engineering, or related field.
- Strong programming skills in Python and/or R.
- Expertise in SQL and database technologies.
- Experience with ML frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost.
- Experience with cloud platforms: Azure, AWS, Google Cloud.
- Knowledge of data warehousing, data lakes, ETL/ELT pipelines, Spark and distributed computing.
- Familiarity with MLOps tools: MLflow, Azure ML, Databricks, Kubernetes, Docker.
- Experience with Generative AI, LLMs, Prompt Engineering, and RAG architectures.
- Strong understanding of statistics, probability, experimental design, time series analysis, optimization.
Responsibilities
- Develop analytics to address customer needs and opportunities.
- Translate algorithms into commercially viable products and services with software teams.
- Work in technical teams on development, deployment, and application of analytics.
- Perform exploratory data analyses using descriptive statistics.
- Collaborate with data engineers on data quality and data cleansing.
- Generate reports and artifacts to document the work and outcomes.
- Analyze large structured and unstructured datasets to identify trends and opportunities.
- Develop statistical models to uncover insights and support business decisions.
- 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, RAG, and Agentic AI techniques where applicable.
- Evaluate model performance and improve accuracy and reliability.
- Build scalable data pipelines for ingestion, transformation, and feature engineering.
- Implement model deployment, monitoring, and lifecycle management using MLOps.
- Work with cloud-native AI and data platforms.
- Ensure data quality, governance, security, and compliance.
- Collaborate with stakeholders to define success metrics and translate business problems into AI solutions.
- Present technical findings to technical and non-technical audiences.
- Measure business impact of deployed solutions and stay current with AI advancements.
Skills
Education
Tools
Job description
Are you a highly motivated, creative individual and passionate about Data Science? Would you like to be a part of successful team? Join our team!
- 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 in 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 your 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 (EDA) 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 (RAG), 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 both technical and non-technical audiences.
- Measure and communicate 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.
- Fuel your passion!
- Bachelor's or master's degree in data science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
- Technical skills – Strong programming skills in Python and/or R.
- Expertise in SQL and database technologies.
- Experience with machine learning frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost.
- Experience with cloud platforms: Microsoft Azure, AWS, Google Cloud Platform.
- Knowledge of: Data Warehousing, Data Lakes, ETL/ELT pipelines, Spark and distributed computing.
- Familiarity with MLOps tools: MLflow, Azure ML, Databricks, Kubernetes, Docker.
- Experience with Generative AI, LLMs, Prompt Engineering, and RAG architectures.
- Strong understanding of: Statistics, Probability, Experimental Design, Time Series Analysis, Optimization Techniques.
- Experience deploying AI solutions into production environments.
- Knowledge of Responsible AI, AI governance, and model explainability.
- Experience with vector databases (Pinecone, Azure AI Search, Weaviate, Chroma).
- Familiarity with AI agents and autonomous workflows.
- Industry knowledge in domains such as healthcare, finance, retail, manufacturing, or telecommunications.
- Strong problem-solving and critical-thinking abilities.
- Excellent communication and storytelling skills.
- Ability to work in cross-functional teams.
- Strategic mindset with a focus on business outcomes.
- Continuous learning and innovation mindset.
- Delivers measurable business value from AI and analytics initiatives.
- Builds scalable and production-ready ML/AI solutions.
- Improves operational efficiency through data-driven automation.
- Drives adoption of AI technologies across the organization.
- Maintains high standards of governance, security, and responsible AI.
We recognize that everyone is different and that the way in which people want to work and deliver at their best is different for everyone too.
Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
- Contemporary work-life balance policies and wellbeing activities.
- Comprehensive private medical care options.
- Safety net of life insurance and disability programs.
- Tailored financial programs.
- Additional elected or voluntary benefits.
Our people are at the heart of what we do at Baker Hughes. We know we are better when all of our people are developed, engaged and able to bring their whole authentic selves to work.
We invest in the health and well-being of our workforce, train and reward talent and develop leaders at all levels to bring out the best in each other.
We believe in creating an environment of diversity and inclusion, without bias.
The Baker Hughes internal title for this role is: Digital Technology Specialist - Data Science.
At Baker Hughes, we are transforming the future of energy. With operations in over 120 countries, we are developing and deploying industry-leading technologies and services to take energy forward.
For more than a century, our inventions have revolutionised energy. Today, we are bringing our expertise to make oil and gas safer, cleaner, and more efficient.
Our people are the trusted experts, relied on to solve customer challenges big and small. We invest in the health and well-being of our workforce, train and reward talent, and develop leaders at all levels to bring out the best in each other.
We believe in creating an environment of diversity and inclusion, without bias. We know we are better when all of our people are developed, engaged, and able to bring their whole authentic selves to work. We're makers, inventors, and leaders who aren't afraid of the tough challenges. We believe pushing boundaries will help to lead the way for a new energy future.
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