I applied online for a Data Scientist position, the process began with an initial recruiter screening focused on my background, work authorization, interest in the role, and salary expectations. After the screening, I was invited to a virtual hiring manager interview with two members of the team. The interview lasted approximately one hour and was primarily behavioral and situational, with a few technical questions related to data science workflows, machine learning, analytics, SQL, Python, model deployment, stakeholder communication, and project experience. The interviewers placed significant emphasis on the STAR (Situation, Task, Action, Result) format and asked multiple questions around teamwork, communication, problem solving, conflict resolution, initiative, and translating technical work into business impact. The technical discussion focused more on practical applications of data science rather than coding exercises or algorithm-heavy questions. Overall, the interview experience was professional and conversational. Candidates should be prepared to discuss past projects in depth, explain their decision-making process, and demonstrate how they have applied analytics and machine learning to solve real business problems.