Role Overview
We are seeking a experienced AI Engineer / Python Developer to design, develop, and deploy intelligent systems leveraging machine learning and advanced analytics. The ideal candidate will have robust expertise in Python libraries, Core Machine Learning, Decision Trees, and Pattern Recognition, and be capable of translating complex business problems into scalable AI-driven solutions within the financial/regulated ecosystem.

Key Responsibilities

1. AI/ML Solution Development

Design and implement machine learning models including decision trees, classification, regression, and clustering algorithms
Develop scalable AI pipelines for pattern recognition, anomaly detection, and predictive analytics
Translate business requirements into robust ML models and deployment strategies

2. Python Development & Libraries

Build high-performance applications using Python and libraries such as:

- NumPy, Pandas Data manipulation and preprocessing
- Scikit-learn ML model development (especially decision trees)
- TensorFlow / PyTorch – Deep learning (if applicable)
- Matplotlib / Seaborn – Data visualization
- Write clean, modular, and production-grade Python code

3. Pattern Recognition & Analytics

Implement algorithms for pattern identification, classification, and behavioral analysis
Apply statistical and machine learning techniques for:

- Transaction pattern analysis
- Fraud detection scenarios (relevant for financial domain)
- Data segmentation and clustering

4. Model Training & Optimization

- Train, validate, and fine-tune ML models for performance improvement
- Optimize models for accuracy, latency, and scalability
- Perform feature engineering and selection

5. Data Handling & Engineering

- Work with structured and semi-structured datasets
- Develop pipelines for data ingestion, cleaning, transformation, and feature extraction
- Ensure data quality, integrity,



and compliance with regulations

6. Deployment & Integration

- Deploy ML models into production environments using APIs or microservices
- Integrate AI solutions with existing enterprise systems and workflows
- Monitor model performance and implement continuous improvement

7. Collaboration & Stakeholder Engagement

- Collaborate with business teams, architects, and data engineers
- Participate in requirement discussions and solution design
- Document models, processes, and results for internal stakeholders

Required Skills & Qualifications

Technical Skills

- Strong programming expertise in Python.
- Experience with machine learning algorithms, especially: Decision Trees, Random Forests
Classification and regression models.
- Hands-on experience in pattern recognition techniques.
- Proficiency in Python ML libraries: Scikit-learn (mandatory),Pandas, NumPy
- Understanding of core ML concepts:

* Model evaluation metrics (accuracy, precision, recall, F1 score)
* Bias-variance tradeoff
* Cross-validation techniques

Additional Preferred Skills

- Exposure to deep learning frameworks (TensorFlow, PyTorch)
- Experience with NLP or computer vision (nice to have)
- Knowledge of SQL and databases
- Experience in financial services / capital markets domain (highly desirable)
- Familiarity with cloud platforms (Azure, AWS, or GCP) for ML deployments

Educational Qualifications

Bachelor’s or Master’s degree in:

- Computer Science
- Data Science
- Artificial Intelligence
- Engineering or related field

Soft Skills

- Robust analytical and problem-solving ability
- Effective communication and stakeholder management
- Ability to work in a fast-paced, regulated environment
- Attention to detail and commitment to quality

Key Deliverables:

- High-quality AI/ML models for business use cases
- Efficient Python-based ML solutions
- Documentation for models, pipelines, and deployment
- Continuous improvement in model performance

📌 AI Engineer & Python Developer (Maharashtra)
🏢 Cognizant
📍 Maharashtra