FACE Prep
Website:
faceprep.in
Job details:
Company Description FACE Prep is one of India’s 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 preparation, workshops, and bootcamps. The organization focuses on building industry-relevant skills that enable learners to secure top-paying roles in technology. FACE Prep’s alumni are employed across leading global 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 workplace expectations.
Role Description This is a full-time, on-site freelance role for a Data Science / ML Trainer based in Bengaluru. The trainer will design and deliver engaging classroom sessions on data science, statistics, data analytics, and machine learning concepts tailored for placement-focused learners. Responsibilities include preparing curricula and teaching materials, creating hands-on projects and case studies, and guiding students through practical exercises and assessments. The role involves evaluating learner performance, providing constructive feedback, and mentoring students on career paths and interview preparation for data-focused roles. The trainer will also collaborate with internal teams to update content based on industry trends and employer requirements.
Qualifications
- Strong foundation in Data Science and Machine Learning, with the ability to explain complex concepts in a clear and structured manner.
- Proficiency in Data Analytics and Data Analysis, including working with real-world datasets, exploratory analysis, and insights generation.
- Solid Statistics and Analytical Skills to design rigorous learning modules, assessments, and problem-solving sessions.
- Experience with relevant tools and languages such as Python or R, common ML libraries (e.g., scikit-learn, pandas, NumPy), and data visualization tools.
- Prior teaching, training, or mentoring experience, preferably with college students or early-career professionals in technical domains.
- Excellent communication and presentation skills, with the ability to engage diverse learners and manage classroom interactions effectively.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field.
- Familiarity with industry expectations for data roles, including placement preparation, technical interviews, and project portfolios.
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