Manager/Deputy/Assistant Infotech

Responsibilities & Key Deliverables

a. Data Analysis: Conduct thorough data analysis to extract meaningful insights and support decision-making processes.
b. Model Development: Design, develop, and deploy predictive models using machine learning and statistical techniques.
c. Model Engineering: Experience with deploying and operationalizing machine learning models, including familiarity with relevant tools and platforms like ML pipelines, cloud services, containerization (Docker), and proficiency in integrating models into production systems, alongwith the standard skills like data cleaning, feature engineering, and model selection. 
d. Performance Monitoring: Monitor and evaluate the performance of models (using Metrices) in production, and implement improvements as needed.
e. Documentation: Maintain detailed documentation of data processes, models, and methodologies for future reference.

Preferred Industries

Education Qualification

BE-Tech (Computer Science)/MCA, Google Cloud Professional ML Engineer

General Experience

5 years of relevant in developing and deploying ML Models

Critical Experience

a. Proficiency in programming languages such as Python, Web frameworks like Flask or Streamlit and SQL database.
b. Statistical Knowledge: Strong understanding of statistical methods, probability, and data distributions.
c. Machine Learning: Experience with machine learning frameworks and libraries like TensorFlow, scikit-learn, and PyTorch.
d Data Wrangling: Expertise in data cleaning, transformation and feature engineering.
e. Analytical Skills: Excellent problem-solving and analytical thinking abilities.
f. Familiarity with Bitbucket for version control.
g. Experience with cloud platforms (e.g., AWS, Google Cloud) and containerization (e.g., Docker).
h. Familiarity with natural language processing (NLP), Computer vision, reinforcement learning and other advanced AI techniques.

System Generated Core Skills

System Generated Secondary Skills