Data Scientist applying machine learning and statistical models for HP's Enterprise Planning & Analytics team. Leading diverse data projects focused on demand planning and forecasting.
About the role
- Data Scientist developing AI/ML models for Hummingbird. Collaborating with stakeholders to enhance data-driven business solutions.
Responsibilities
- Designing and developing AI/ML models that significantly accelerate the delivery of business value
- Working with business stakeholders to prototype and deliver innovative data science applications
- Combining expertise in mathematics, statistics, computer science, and domain knowledge to create AI/ML models
- Collaborating closely with the AI Technical Manager and GCC Petro-technical professionals and data engineers to integrate models into the business framework
- Identifying and framing opportunities to apply advanced analytics, modeling, and related technologies to data
- Understanding and communicating the value of proposed opportunities with team members and stakeholders
- Cleaning data and developing and testing models
- Establishing the life cycle management process for models
- Providing technical mentoring in modeling and analytics technologies
- Driving innovation in AI/ML to enhance capabilities in data-driven decision-making
- Aligning with team on shared goals and outcomes and recognizing others’ contributions
Requirements
- Bachelor’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field
- Proven experience in Data Science / AI / Machine Learning roles
- Strong foundation in mathematics, statistics, and data analysis
- Proficiency in programming languages such as Python (preferred) or R
- Hands-on experience in building, testing, and deploying AI/ML models
- Experience in data cleaning, feature engineering, and model evaluation techniques
- Familiarity with machine learning frameworks/libraries (e.g., Scikit-learn, TensorFlow, PyTorch)
- Experience working with large and complex datasets
- Strong understanding of data modeling, predictive analytics, and statistical techniques
- Experience collaborating with cross-functional teams (data engineers, business stakeholders, technical leads)
- Ability to translate business problems into data-driven solutions
- Strong communication skills with the ability to explain technical concepts to non-technical stakeholders
- Experience in end-to-end model lifecycle management (development, deployment, monitoring)
- Exposure to cloud platforms (e.g., AWS, Azure, or GCP) is a plus
- Experience in mentoring or guiding junior team members is an advantage
- Strong problem-solving skills, adaptability, and ability to work in a fast-paced, evolving environment
Benefits
- Broad exposure to the application of technology
- Opportunities for growth and professional development
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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