Data Scientist-Paytm Money

Paytm Money is looking for a talented and results-driven Data Scientist to join our analytics and AI/ML team in Mumbai. The ideal candidate will have 5-8 years of experience in developing data-driven solutions, implementing machine learning models, and working on large-scale financial data systems. This role is critical to enhancing Paytm Money's investment and financial services platform with cutting-edge AI/ML technologies.

Role & responsibilities

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 ne ones.
• Natural Language Processing (NLP): Implement basic NLP techniques, such as text
• processing, sentiment analysis, and feature extraction.

Key Requirements:

1. Experience & Domain Knowledge:
   
• 5-8 years of experience as a Data Scientist, preferably in fintech, investment, or financial services domains.
• Strong knowledge of capital markets, mutual funds, trading, or other financial instruments.
2. Technical Skills:
   
• Proficiency in Python and libraries like Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Strong command over SQL for querying large datasets.
• Hands-on experience with big data technologies (e.g., Spark, Hadoop, Hive).
• Knowledge of visualization tools like Tableau, Power BI, or Matplotlib/Seaborn.
3. Machine Learning Expertise:
   
• Proven experience in developing and deploying supervised and unsupervised learning models.
• Knowledge of natural language processing (NLP) and deep learning is a plus.
• Familiarity with recommendation systems, time-series analysis, and anomaly detection.
4. Tools & Platforms:
   
• Experience with cloud platforms like AWS, Google Cloud Platform (GCP), or Azure.
• Familiarity with version control systems like Git.
5. Soft Skills:
   
• Strong analytical and problem-solving skills.
• Excellent communication skills to convey technical findings to non-technical stakeholders.
• Ability to work in a fast-paced, dynamic environment and meet deadlines.

Preferred Qualifications:

• A Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related field.
• Certifications in Data Science, AI/ML, or relevant financial technologies.
• Experience working in startups or fast-scaling organizations.