Data Science Faculty

Company Description FACE Prep is one of Indias largest placement-focused skill development companies, specializing in job preparation for the tech sector. Since 2008, FACE Prep has helped millions of students launch their careers through masterclasses, self-paced programs, and intensive workshops or bootcamps. The organization focuses on equipping learners with practical skills that align with the requirements of top-paying technology roles. FACE Preps alumni work across leading global tech companies such as Google, Microsoft, Meta, Adobe, PayPal, Amazon, TCS, Infosys, Wipro, Thoughtworks, Cognizant, and Accenture. The team is driven by a mission to bridge the gap between academic learning and industry expectations.

Role Description This is a full-time, on-site Data Science Faculty role based in Bengaluru. The Data Science Faculty will design and deliver engaging classroom sessions on core data science concepts, tools, and techniques, aligned with FACE Preps curriculum and learning outcomes. Day-to-day responsibilities include preparing teaching materials, creating assignments and projects, conducting assessments, and providing constructive feedback to learners. The faculty member will mentor students on career paths in data science, guide them through interview preparation, and support their readiness for placement opportunities. The role also involves collaborating with the academic team to update course content, integrating industry trends and real-world use cases, and participating in workshops or bootcamps as needed.

Qualifications

• Candidates should possess strong knowledge of data science fundamentals, including statistics, data analysis, and machine learning concepts.
• Candidates should possess practical skills in programming languages and tools commonly used in data science (for example, Python or R, relevant libraries, and data visualization tools).
• Candidates should possess experience with real-world data projects, such as data cleaning, feature engineering, model building, and performance evaluation.
• Candidates should possess clear and structured communication skills, with the ability to explain complex topics in an accessible and engaging manner.
• Candidates should possess demonstrated teaching, training, or mentoring experience, preferably with college students or early-career professionals.
• Candidates should possess strong classroom management and facilitation skills, including the ability to handle doubts, encourage participation, and adapt teaching style to different learner levels.
• Candidates should possess familiarity with current industry practices in data science, analytics, and AI, and an interest in continuous learning and curriculum improvement.
• Relevant academic qualifications such as a masters degree in Computer Science, Data Science, Statistics, or a related field are preferred; industry certifications or a strong project portfolio are an added advantage.