Veraxion
Azure Data Scientist
- Compensation
- Not disclosed
- Location
- Bangalore
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data science
- Posted
Skills
Must have
- 5 years in designing and developing AI/ML models.
- Solid foundation in mathematics, probability, and statistics with demonstrated depth of knowledge and experience in advanced analytics and data science methodologies (e. g., supervised and unsupervise
- Proficiency in Python and working knowledge of cloud AI/ML services (Azure Machine Learning and Databricks preferred).
- Domain knowledge relevant to the energy sector and working knowledge of the Oil and Gas value chain (e. g., upstream, midstream, or downstream) and associated business workflows.
- Proven ability to frame data science opportunities, leverage standard foundational tools and Azure services to perform exploratory data analysis (for purposes of data cleaning and discovery), visualis
- Ability to quickly assess current state and apply technical concepts across cross-functional business workflows.
- Experience with driving successful execution, deliverables, and accountabilities to meet quality and schedule goals.
- Ability to translate complex data into actionable insights that drive business value.
- Demonstrated ability to engage and establish collaborative relationships both inside and outside the immediate workgroup at various organisational levels, across functional and geographic boundaries t
- Demonstrated ability to adjust behaviour based on feedback and provide feedback to others.
- Team-oriented mindset with effective communication skills and the ability to work collaboratively.
Full description
We are looking for a highly skilled Senior Data Scientist / AI-ML Engineer with 5+ years of experience in designing and developing AI/ML models, advanced analytics, and data science solutions. The role involves hands-on work with Python, statistical modelling, exploratory data analysis, and cloud AI/ML technologies such as Azure Machine Learning and Databricks. The ideal candidate will have strong Energy/Oil & Gas domain knowledge, the ability to translate complex data into actionable business insights, and experience collaborating with cross-functional teams to deliver scalable, high-quality solutions aligned with business goals.
Responsibilities:
- Combine expertise in mathematics, statistics, computer science, and domain knowledge to create AI/ML models to solve various Chevron business challenges.
- Collaborate closely with the AI Technical Manager and GCC Petro-technical professionals and data engineers to integrate models into the business framework.
- Identify and frame opportunities to apply advanced analytics, modelling, and related technologies to data to help Chevron businesses gain insight and improve decision-making, workflow, and automation.
- Understand and communicate the value of proposed opportunities with team members and other stakeholders.
- Identify needed data and appropriate technology to solve identified business challenges.
- Clean data and develop and test models.
- Establish the life cycle management process for models.
- Provide technical mentoring in modelling and analytics technologies, the specifics of the modelling process, and general consulting skills.
- Drives innovation in AI/ML to enhance Chevron's capabilities in data-driven decision-making.
- Aligns with the team on shared goals and outcomes, recognises others' contributions, and works collaboratively and seeks diverse perspectives.
- Takes actions to develop self and others beyond existing skill sets.
- Encourages innovative ideas, adapts to change and changing technologies.
- Understands and communicates data, insights, and model behaviours to stakeholders with varying levels of technical expertise.
Requirements:
- 5 years in designing and developing AI/ML models.
- Solid foundation in mathematics, probability, and statistics with demonstrated depth of knowledge and experience in advanced analytics and data science methodologies (e. g., supervised and unsupervised learning, statistics, data science model development).
- Proficiency in Python and working knowledge of cloud AI/ML services (Azure Machine Learning and Databricks preferred).
- Domain knowledge relevant to the energy sector and working knowledge of the Oil and Gas value chain (e. g., upstream, midstream, or downstream) and associated business workflows.