Job Description
Paytm Money is seeking a skilled and detail-oriented Data Scientist with 3+ years of experience. The ideal candidate will possess strong programming skills in Python, expertise in data manipulation, image processing, and machine learning. This role involves understanding and enhancing existing data science solutions, building pipelines, and contributing to the development of new models. Responsibilities include developing and maintaining Python-based data processing scripts and pipelines, designing and implementing automated Python pipelines and cron jobs for data ingestion and analysis, writing and optimizing SQL queries, applying image processing techniques using OpenCV, managing code with Git, building and deploying machine learning models using TensorFlow or PyTorch, and implementing basic NLP techniques.
Good To Have:
- Natural Language Processing (NLP)
Must Have:
- Python Programming
- Pipeline Development
- SQL
- Image Processing
- Version Control (Git)
- Machine Learning
- Deep Learning
We are looking for a skilled and detail-oriented Data Scientist with 3+ years of experience to join
our team. The ideal candidate should have a strong programming background in Python and
have experience in data manipulation, image processing, and machine learning. This role will
focus on understanding and improving our existing data science solutions, building pipelines,
and also contributing to the development of new models.
Responsibilities and Skills:
* Python Programming: Develop, maintain, and automate Python-based data processing scripts
and pipelines using libraries such as Pandas, NumPy, and Matplotlib.
* Pipeline Development: Design and implement automated Python pipelines and cron jobs for
data ingestion and analysis.
* SQL: Write and optimize SQL queries for data analysis and manipulation.
* Image Processing: Apply image processing techniques using OpenCV, including working with
contours and morphological transformations.
* Version Control: Proficient in Git, managing code for merging, building processes, and
handling large and diverse projects effectively.
* Machine Learning and Deep Learning: Build, evaluate, and deploy machine learning models
using frameworks like TensorFlow or PyTorch, improving existing solutions or creating new
ones.
* Natural Language Processing (NLP): Implement basic NLP techniques, such as text
processing, sentiment analysis, and feature extraction.
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