Data Science Trainer Sme

Data Science Trainer cum SME

LNT/DSTCS/1197123

EdutechChennai Manapakkam
- Posted On
11 Nov 2024- Required Experience
8 - 20 Years**Skills**:
Knowledge & Posting Location

DATA SCIENCE - AI

DATA SCIENCE

Minimum Qualification

BACHELOR OF COMPUTER APPLICATION (BCA)

POST GRADUATE DIPLOMA IN COMPUTER SCIENCE

MASTER OF COMPUTER SCIENCE (MCS)

MASTER OF COMPUTER APPLICATIONS (MCA)

**Job Description**:
**_ Job Summary:_**

**_ Key Responsibilities:_**
- ** Training**:Conduct regular training sessions and workshops for internal teams to enhance their skills and knowledge in AI, data science, and data engineering.
- ** Content Development**: Create high-quality educational materials, tutorials, and documentation on AI, data science, and data engineering topics including PySpark, Scala, and Hadoop.
- ** Content Review**: Review and provide feedback on existing content to ensure technical accuracy and clarity.
- ** Collaboration**: Work with instructional designers, educators, and technical writers to develop comprehensive and engaging learning modules.
- ** Research**: Stay current with the latest advancements in AI, data science, and data engineering to ensure content remains up-to-date and relevant.
- ** Mentorship**: Provide guidance and mentorship to team members and learners on complex AI and data engineering topics.
- ** Quality Assurance**: Ensure all content meets the highest standards of accuracy, clarity, and pedagogical effectiveness.

**_ Required Skills and Qualifications:_**
- ** Education**: Bachelor’s or Master’s degree in Computer Science, Data Science, Data Engineering, or a related field.
- ** Experience**: Proven experience as a practitioner or researcher in AI, data science, and data engineering with significant experience in training and mentoring.

**_ Technical Skills:_**
- ** Programming Languages**: Python, Scala
- ** Big Data Technologies**:Hadoop (including HDFS, MapReduce, Hive), PySpark, Spark
- ** Data Engineering**:Data collection, preprocessing, and transformation, Data pipeline creation and maintenance, ETL processes (Extract, Transform, Load)
- ** Machine Learning**:Knowledge of various machine learning algorithms and models, Experience with frameworks such as TensorFlow, PyTorch, Keras, and scikit-learn
- ** Data Science**:Statistical analysis and modeling, Data visualization tools and techniques, Exploratory data analysis
- ** Model Deployment**:Experience in deploying machine learning models in production environments
- ** Cloud Platforms**:Familiarity with AWS, Azure, or Google Cloud and their AI/ML and big data services

**_ Analytical and Problem-Solving Skills:_**
- ** Analytical Thinking**: Ability to break down complex problems and identify solutions using AI and data engineering techniques.
- ** Problem Solving**: Strong problem-solving skills to tackle challenging AI/data engineering issues and optimize models.

**_ Communication and Collaboration Skills:_**
- ** Written Communication**: Excellent writing skills to create clear, concise, and engaging content on AI and data engineering topics.
- ** Verbal Communication**: Ability to explain complex concepts to non-experts in an accessible manner.
- ** Collaboration**: Experience working with cross-functional teams, including instructional designers, educators, and technical writers.

**_ Educational and Content Development Skills:_**
- ** Teaching and Mentoring**: Experience in teaching or mentoring others in AI/data engineering topics.
- ** Content Creation**: Experience in developing educational materials, tutorials, technical documentation, and guides.
- ** Content Review**: Skills in reviewing and providing feedback on technical content to ensure accuracy and clarity.

**_ Research Skills:_**
- ** Staying Updated**: Keeping up with the latest trends, research, and developments in AI, data science, and data engineering.

**_ Preferred Qualifications:_**
- ** Advanced Degree**: A Master’s or Ph.D. in Computer Science, Data Science, Data Engineering, or a related field.
- ** Publication Record**: Experience in publishing research papers or technical articles in AI, data science, or data engineering.
- ** Additional Big Data Tools**: Knowledge of other big data tools and technologies like Kafka and Flink.

**_ Interpersonal Skills:_**
- ** Team Player**: Ability to work effectively as part of a team.
- ** Adaptability**: Flexibility to adapt to changing requirements and technologies.
- ** Attention to Detail**: High attention to detail to ensure accuracy and quality in content development.