Data Science Trainer
3 days ago
Location: Indore
Exp: 4-5 years
Experience
1. Essential Criteria:
Training Delivery: Conduct engaging and interactive training sessions, workshops, and webinars on AI topics such as machine learning, natural language processing, computer vision, responsible AI, and AI applications in specific sectors (e.g., education, health, governance).
Assessment & Evaluation: Develop and administer assessments to evaluate participants' understanding and application of AI concepts. Provide feedback and guidance to ensure learning objectives are met.
Continuous Improvement: Stay up-to-date with the latest developments in AI and integrate new knowledge into training materials. Continuously improve training programs based on participant feedback and evolving industry trends.
Curriculum Development: Design and develop comprehensive AI training curriculums tailored to different audiences, including basic, intermediate, and advanced levels of AI literacy.
Customization: Adapt training content to meet the specific needs of different audiences, including policymakers, healthcare workers, teachers, students, climate experts, and industry professionals.
Content Creation: Create high-quality training materials, including presentations, hands-on exercises, case studies, and assessments that align with learning objectives.
Experience of writing code to automate current system workflow, especially in R or Python
for data analysis, Predictive modelling, Predictive analytics.
Experience in research, transform, design, and implement data science prototypes to automate system process with help of various ML Algorithm and tools.
Automate multiple processes in Data science related to Hyperparameter optimization, Model selection, Feature selection, Data pre-processing, Testing and validation of multiple models.
Hands-on working in platform like R (R Studio)/Python (Jupiter notebooks, spyder)
Analysing the business requirements and mapping out how automation will be implemented.
Analysing data and testing the developed automated solutions outcome to ensure it complies with management expectations and standards.
Experience of working on end-to-end data science pipeline: problem statement, data gathering, EDA, modelling, data visualization, validation, monitoring, and maintenance
Experience in research, design, and builds self-running AI systems for automating predictive models.
Experience using machine learning algorithms (e.g., Multivariate regression, OLS, Ridge regression, Lasso regression, Boosting, Neural Network)
Knowledge of working with Git.
2. Desirable Criteria:
Experience of predictive analytics and ML modelling.
Experience in deep learning, NLP
Knowledge:
1. Essential Criteria:
Advance knowledge of statistics, Data science and Machine learning
Knowledge of automation and implementation tools.
Knowledge of Multiple Linear Regression Technique, Data Mining Methodology.
Knowledge of Predictive Analytics and Machine Learning concepts and algorithms
Knowledge to automate current process in system by using ML algorithms.
2. Desirable Criteria:
Knowledge of Advance Machine Learning Technique
Skills:
1. Essential Criteria:
Excellent numerical/ statistical/ mathematical skills
Excellent skills with R/Python for data analysis, Advance Excel, predictive modelling
Ability to think in automate way to solve business problem with complex dataset.
Ability to identify and fix bugs in data sets and code.
Strong team working and critical thinking skills.
Ability to manage own workload.
Ability to build positive relation within organisation with managers.
Ability to deliver trainings.
Excellent written and oral communication skills.
2. Desirable Criteria:
Professional, dependable, solid work ethic, detail-oriented, self-motivated.
Strong analytical and problem-solving skills
Responsibilities:
Ability to understand a problem statement and implement analytical solutions and technique independently and proactively.
Design and build Artificial Intelligence algorithms with self-learning capabilities to make precise predictions for next-level automation.
Ability to identify opportunity for leveraging company data to drive business solutions.
Conceptualize, design, and implement high quality solutions and insightful analysis.
Conduct research and prototyping innovations, Data and requirement gathering, solution
scoping and maintain process flow on advance statistical and machine learning problems.
Collaborate and coordinate with different functional teams to implement models and monitor outcomes.
Ability to research, design, development and implement AI/ML based solution.
Ability to script codes in R/Python and analyse large datasets to uncover answer to complex
problems based on Real Estate domain.
Analyse raw data, Perform data processing functions of structured and unstructured data.
Analyse and identify scope of automation in large amount of information to discover hidden trends and pattern in the dataset, Data Cleaning, Data Pre-processing, Data visualization, Exploratory Data Analysis, Model Building and Generate reports in R Markdown
Ability to break the problem into small parts and applying relevant technique to drive relevant outcome.
Ability to learn and pick up new language / tool / platform quickly.
Identify areas of improvement and create solutions for those areas.
Qualifications:
Graduate / Post Graduate (B.Tech.(CS/IT), Mathematics, Statistics)
Minimum of 4-5 years’ of full-time professional working experience in developing data science
models
Interested candidates can share their CVs to
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