Tech StaQ

Overview
A leading financial services organization is seeking an experienced Data Scientist with deep expertise in AI, machine learning, and Python development. You design, build, and deploy scalable data-driven models that solve complex business challenges and drive strategic decision-making. This role partners closely with cross-functional stakeholders to transform data into actionable insights.

Key Responsibilities

• Data Collection & Preparation
• Ingest, clean, and preprocess large structured and unstructured datasets from multiple sources
• Perform exploratory data analysis (EDA) to identify trends, patterns, and data quality issues
• Develop and maintain robust ETL pipelines for efficient data transformation
• Model Development & Deployment
• Architect, train, and deploy supervised, unsupervised, and deep learning models (classification, regression, clustering)
• Optimize model performance (accuracy, latency, scalability) using advanced frameworks (TensorFlow, PyTorch, Scikitlearn)
• Automate model retraining and monitoring workflows in production environments
• Algorithm Engineering
• Design and refine algorithms for large-scale data processing and real-time inference
• Implement best practices for model interpretability, fairness, and reliability
• Software Engineering & Integration
• Write clean, modular Python code following industry standards (Pandas, NumPy, SciPy)
• Integrate models into existing software platforms and cloud infrastructure (AWS, GCP, Azure)
• Maintain version control (Git) and CI/CD pipelines for reproducible deployments
• Evaluation & Validation
• Define and track key performance metrics (accuracy, precision, recall, F1)
• Conduct rigorous cross-validation, A/B testing, and stress testing to ensure robustness
• Collaboration & Communication
• Translate business requirements into technical specifications and actionable analytics solutions
• Present complex findings clearly to technical and non-technical stakeholders
• Document methodologies, code, and model decisions for transparency and audibility

Required Qualifications

• 4+ years in a Data Scientist or Machine Learning Engineer role
• Mastery of Python and core libraries (Pandas, NumPy, Scikitlearn)
• Hands-on experience with deep learning frameworks (TensorFlow or PyTorch)
• Solid understanding of statistical modeling, feature engineering, and model evaluation
• Proficiency with data visualization tools (Matplotlib, Seaborn, Plotly)
• Experience deploying models on cloud platforms (AWS, GCP, or Azure)
• Bachelors or Masters degree in Computer Science, Data Science, Mathematics, or related field

Preferred Skills

• Expertise in Natural Language Processing (NLP) or Computer Vision
• Familiarity with big data technologies (Spark, Hadoop)
• Knowledge of containerization (Docker/Kubernetes)
• Experience working in Agile/Scrum environments
• Strong written and verbal communication skills

What We Offer

• Opportunity to influence high-impact data initiatives
• Collaborative, crossdisciplinary work environment
• Professional development and certification support
• Flexible work arrangements and competitive benefits package