Lead Data Scientist

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

We are seeking aData Scientist with strong downstream refining experienceto drive data-driven insights across refinery operations, economics, and reliability. This role partners closely with process engineers, operations, planning, maintenance, and commercial teams to optimize refinery performance using advanced analytics, machine learning, and domain-informed modeling.

Youll work on high-impact problems such as yield optimization, energy efficiency, unit reliability, predictive maintenance, and margin improvementturning complex refinery data into actionable intelligence.

Key Responsibilities

Analytics & Modeling

• Develop, validate, and deploystatistical, ML, and optimization modelsfor refining operations
• Build models supporting:

• Unit performance optimization (e.g., CDU/VDU, hydrotreating, cracking)
• Energy efficiency and utilities optimization
• Yield and cut-point optimization
• Predictive maintenance and reliability analytics
• Fouling, corrosion, and anomaly detection

• Apply time-series analysis to high-frequency plant data (DCS, historian)

Refining Domain Collaboration

• Partner withprocess engineers, operations, maintenance, and planning teamsto translate refinery problems into analytical solutions
• Incorporatefirst-principles knowledge(mass & energy balances, constraints, process limits) into data models
• Interpret model results in the context of refinery economics, safety, and operability

Communication & Impact

• Clearly communicate insights totechnical and non-technical stakeholders
• Quantify business impact (margin improvement, energy reduction, reliability gains)

Requirements

• Bachelors or Masters degree inData Science, Chemical Engineering, Applied Mathematics, Statistics, or related field
• 38+ yearsof experience applying data science indownstream refining or closely related process industries
• Strong proficiency inPython or Rfor data analysis and modeling
• Experience withtime-series dataand industrial process data
• Solid understanding ofrefining processes and unit operations
• Experience working withhistorians (PI), SQL databases, and unstructured data

Preferred Qualifications

• Advanced degree (MS or PhD)
• Familiarity with:

Optimization techniques (LP/NLP)

Digital twin or hybrid physics + ML models

Cloud platforms (AWS, Azure, GCP)nced Data Scientists.

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.