Data Scientist

About The Company

Oracle is a global technology leader renowned for its innovative solutions in cloud computing, database management, and enterprise software. With a rich history of pioneering advancements, Oracle empowers organizations across various industries to optimize their operations, enhance security, and accelerate digital transformation. The company’s commitment to excellence, innovation, and customer success has established it as a trusted partner in the technology space. Oracle’s extensive portfolio includes cloud infrastructure, software applications, and hardware systems designed to meet the evolving needs of modern enterprises.

About The Role

Oracle is collaborating with Hackajob to connect with exceptional professionals for the role of Senior Data Scientist within the Oracle Cloud Infrastructure (OCI) Data Science and Analytics team. This position offers an exciting opportunity to work at the forefront of cloud infrastructure innovation, focusing on building sophisticated analytical solutions that enhance operational efficiency and support global expansion efforts. The Senior Data Scientist will be instrumental in developing large-scale data pipelines, deploying large language models (LLMs), and driving data-driven initiatives that directly impact OCI’s infrastructure build processes, networking, and data-center materials. The ideal candidate is a strategic thinker who thrives in ambiguous environments, translating complex data into actionable insights and innovative solutions to support OCI’s growth in new regions and markets.

Qualifications

The ideal candidate will possess a strong foundation in data science, statistics, and computer science, with relevant practical experience. A bachelor’s degree or equivalent in Data Science, Statistics, Computer Science, Applied Mathematics, Engineering, Economics, or related fields is required. Candidates should demonstrate proficiency in probability, statistical inference, experimental design, and predictive modeling. Hands-on experience with large-scale data analysis, data warehousing, and working with structured and semi-structured data is essential. Expertise in SQL, Python, or R for data extraction, transformation, and visualization is necessary. Experience developing, validating, and deploying machine learning models, including large language models, is highly preferred. Additionally, familiarity with cloud infrastructure, MLOps, and generative AI solutions will be advantageous. Strong communication skills to articulate insights to technical and non-technical stakeholders are also vital.

Responsibilities

What You'll Do

• Lead exploratory research and conduct rigorous statistical analysis to translate complex data into clear, actionable insights that inform strategic business decisions. Apply data transformation techniques, experimental design, and machine learning methodologies to solve real-world problems.
• Design, optimize, and fine-tune scalable algorithms and models ensuring high reliability, performance, and reproducibility, particularly in high-volume production environments.
• Collaborate closely with data scientists, engineers, product teams, and business stakeholders to define data requirements, evaluate analytical opportunities, and deliver solutions aligned with measurable business outcomes.
• Establish and uphold data quality standards, including validation, monitoring, lineage, and remediation practices, recognizing the importance of reliable data inputs for trustworthy analytics and ML outputs.
• Mentor junior data scientists by sharing best practices in statistical rigor, modeling techniques, experiment evaluation, and effective communication of findings.
• Lead the development, evaluation, and fine-tuning of large language model-based solutions for infrastructure build and data-center materials use cases, including domain adaptation, retrieval strategies, and performance measurement.
• Stay current with advancements in statistics, machine learning, and data science; assess and incorporate emerging techniques to improve business processes, product capabilities, and decision-making quality.
• Continuously update knowledge on the latest developments in AI and data science to apply innovative techniques for process and product enhancements.

Benefits

Oracle offers a comprehensive benefits package designed to support the well-being and professional growth of its employees. This includes medical, dental, and vision insurance, with access to expert medical opinions. Employees are covered under short-term and long-term disability insurance, as well as life insurance and accidental death & dismemberment (AD&D). Supplemental life insurance options are available for employees, spouses, and children. The company provides flexible spending accounts for healthcare and dependent care, along with pre-tax commuter and parking benefits. Oracle’s 401(k) savings and investment plan includes a company match to help employees secure their financial future. Paid time off includes flexible vacation policies, with accrual rates based on tenure, and 11 paid holidays annually. Employees also receive paid sick leave, parental leave, adoption assistance, and access to employee stock purchase plans. Additional voluntary benefits include legal services, auto, home, and pet insurance, among others. Oracle’s benefits are designed to promote a healthy work-life balance and support employees throughout their career journey.

Equal Opportunity

Oracle is an equal opportunity employer committed to fostering an inclusive environment where all employees and applicants are treated with respect and fairness. The company values diversity and encourages individuals of all backgrounds, experiences, and perspectives to apply. Oracle does not discriminate on the basis of race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other protected status. The organization is dedicated to providing equal employment opportunities and ensuring a workplace free from discrimination and harassment.