Data Science Trainer

As a Data Science Trainer, you will be responsible for developing and delivering high-caliber, comprehensive training programs. These programs will empower learners to acquire both practical and theoretical proficiency in the field of data science. You will engage with individuals at various levels of expertise, from beginners to advanced learners, ensuring they acquire the requisite skills to excel in their data science careers.

**Key Responsibilities**:

- **Training Delivery**:

- Deliver engaging, informative, and interactive training sessions—both in-person and online—on a range of data science topics, including machine learning, artificial intelligence, data analytics, and statistical methods.
- Conduct workshops, seminars, and webinars to impart knowledge across diverse learning groups, ensuring clarity and depth in addressing complex technical topics.
- Provide in-depth instruction on data manipulation, cleaning, and preprocessing using key libraries like Pandas, Numpy, Scikit-learn, and TensorFlow.
- Instruct learners on data visualization techniques and tools such as Tableau, Power BI, and Matplotlib, emphasizing their practical utility.
- **Curriculum Development**:

- Design, develop, and refine cutting-edge educational materials, including presentations, coding exercises, case studies, and assessments, ensuring they reflect the latest industry trends and technological advancements.
- Consistently review and improve training curricula based on student feedback, emerging technologies, and market requirements.
- **Student Engagement & Mentorship**:

- Foster a stimulating and supportive learning environment, encouraging active participation, intellectual curiosity, and the exchange of ideas.
- Provide personalized support and mentorship to students, assisting them with technical challenges and career development.
- Host regular office hours, Q&A sessions, and additional learning opportunities to ensure that students feel empowered and confident in their learning journey.
- **Assessment & Progress Evaluation**:

- Develop and administer a range of assessments, including quizzes, coding challenges, exams, and projects, to effectively evaluate student performance and mastery of data science concepts.
- Provide constructive feedback and guidance on student assignments, fostering continuous improvement and mastery.
- Identify learning gaps and tailor remedial support to ensure all students achieve their desired learning outcomes.
- **Industry Engagement & Knowledge Advancement**:

- Stay at the forefront of industry trends, tools, and technologies, ensuring the training content remains cutting-edge and aligned with current market needs.
- Establish partnerships with organizations to offer bespoke corporate training solutions, helping companies upskill their workforce in data science.
- **Administrative Duties**:

- Maintain accurate records of student progress, feedback, and performance metrics.
- Actively contribute to team meetings, curriculum planning, and cross-departmental collaborations.
- Assist with the marketing and promotion of data science training programs, contributing to the growth and success of the organization.

**Qualifications**:

- **Educational Requirements**:

- A bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline. A master’s degree or higher is highly desirable.
- **Professional Experience**:

- A minimum of 3-5 years of hands-on experience in the field of data science training, with a strong focus on machine learning, statistical analysis, and data manipulation.
- Demonstrated experience in teaching, mentoring, or leading training programs, with a track record of effectively delivering complex concepts to a diverse audience.
- Expertise in core data science technologies and platforms, including Python, R, SQL, TensorFlow, Hadoop, and cloud-based platforms such as AWS, Google Cloud, or Azure.
- **Technical Competencies**:

- Profound understanding of data science principles, including predictive modeling, deep learning, data wrangling, and statistical analysis.
- Proficiency in data visualization tools (e.g., Tableau, Power BI, Matplotlib) and the ability to teach students how to communicate data insights effectively.
- Strong knowledge of data science frameworks and libraries, such as Scikit-learn, TensorFlow, Keras, and PyTorch.
- Familiarity with Big Data technologies, including Hadoop, Spark, and distributed computing systems.
- Expertise in advanced programming and scripting languages, with a focus on Python and R.

**Desirable Qualifications**:

- Professional certifications in data science, machine learning, or related fields (e.g., Google Data Analytics, Microsoft Certified: Azure Data Scientist).
- Experience with cloud services and infrastructure for deploying machine learning models.
- Familiarity with Agile methodologies and project management tools.

**Work Location: Somajiguda,Hyderabad.**

**Working Hourse: 9:30AM