Econometrician

Data & Analytics

Data Analyst

US$108,980

Most business decisions start with someone asking a vague question, and a data analyst is the person who turns that question into something a database can answer. The role sits between curiosity and rigor, pulling clean numbers from messy systems and presenting them so a manager can actually decide. Days move between SQL queries, dashboards, and conversations with stakeholders who don't yet know what they need. Strong analysts care about whether the answer is right, not just whether it looks right, which means understanding hypothesis testing and the difference between correlation and cause. Students who enjoy detective work and clear writing grow into this naturally. Tools like Power BI or Tableau become extensions of how you think.

Data & Analytics

Decision Analyst

US$79,349

Imagine a leadership team weighing three product bets, each backed by a different team's confident pitch. A decision analyst is the person who turns that meeting into something rigorous. The role uses Bayesian reasoning, cohort analysis, and causal inference to estimate which choice actually moves the business, and then communicates uncertainty honestly enough that leaders can act anyway. It suits students who love probability puzzles and writing clearly under pressure. Strong decision analysts are remembered for the recommendation that turned out right two years later, even when it was unpopular at the time. You grow into the role through statistics, business literacy, and the discipline of separating what you know from what you assume. Python becomes a thinking tool.

Data & Analytics

IoT Data Scientist

A wind turbine, a hospital infusion pump, a fleet of delivery vans, each one streams telemetry that means nothing until someone extracts a signal from it. IoT data scientists work at that boundary between physical equipment and statistical inference. The role suits students who like the messiness of real-world sensors, missing readings, drift, and all, more than the tidiness of curated datasets. You'd grow into it by combining Python and streaming tools like Apache Kafka with enough hardware literacy to ask engineers the right questions. Anomaly detection becomes a recurring theme. Strong IoT data scientists translate between operations teams who want fewer breakdowns and business stakeholders who want fewer surprises, and that translation work is often where the real value shows up.

Data & Analytics

Machine Learning Engineer

US$121,126

Between a research notebook that proves something might work and a system that serves predictions to millions of users sits the machine learning engineer. Their job is to make models real — reliable, fast, observable, and easy to roll back when something goes sideways. Expect to write production Python, design training pipelines in PyTorch, wire up CI/CD that catches a regression before a customer does, and argue thoughtfully about latency budgets. Students often arrive from data science and discover they enjoy the engineering half more than they expected. Growing into the role means caring about model performance and software craft equally, and treating offline evaluation metrics with the same seriousness as accuracy.

Data & Analytics

Operations Research Analyst

US$79,333

Imagine being asked to schedule a fleet of trucks across a continent, or decide where to place inventory across two hundred warehouses. Operations research analysts use mathematical optimization to answer questions whose search spaces are too large for intuition. The work draws on linear programming, discrete-event simulation in tools like SimPy, and the older traditions of decision analysis and design of experiments. It is a role for students who liked the optimization chapter of their math class and want to apply it to real systems. Growing into it means pairing modeling chops with the patience to validate assumptions against messy reality. Good analysts know when an elegant model is actually answering the wrong question.

Data & Analytics

Process Analyst

US$73,302

Most organizational pain is process pain in disguise. A process analyst is the person who maps how work actually flows — the handoffs, the rework loops, the steps that exist only because someone left three years ago — and proposes changes that stick. The role uses tools like BPMN 2.0 and frameworks like ADKAR, but the real craft is interviewing the people doing the work without making them defensive. Students grow into this through coursework in operations, systems thinking, and early exposure to messy real-world processes. Good process analysts pair root-cause discipline with diplomatic instincts, and write documentation clear enough that the next analyst, two years from now, can pick up where they left off.