Senior Data Scientist

We are seeking an experienced Senior Data Scientist to join our team and drive impactful data-driven solutions across the organization. This role focuses on advanced analytical problem-solving, building sophisticated machine learning models, and delivering insights that directly influence business strategy. The ideal candidate will have deep technical expertise and a proven track record of implementing end-to-end data science solutions.

Key Responsibilities

Model Development & Deployment

• Design, develop, and deploy advanced machine learning and statistical models to solve complex business problems
• Build scalable data pipelines and production-ready ML systems that can handle large-scale data processing
• Implement and optimize algorithms for predictive modeling, classification, clustering, and recommendation systems
• Conduct rigorous model validation, testing, and performance monitoring to ensure reliability and accuracy

Technical Excellence

• Develop and maintain clean, efficient, and well-documented code following best practices
• Optimize model performance through feature engineering, hyperparameter tuning, and algorithm selection
• Implement MLOps practices including model versioning, monitoring, and continuous improvement
• Stay current with the latest developments in data science, machine learning, and AI technologies

Cross-functional Collaboration

• Partner with product managers, engineers, and business stakeholders to identify opportunities for data-driven solutions
• Collaborate with data engineering teams to ensure data quality, accessibility, and infrastructure requirements are met
• Work with software engineers to integrate models into production systems and applications
• Present findings and recommendations to senior leadership and key stakeholders

Required Qualifications

Experience

• 7+ years of professional experience in data science, machine learning, or related analytical roles
• Proven track record of successfully delivering end-to-end data science projects from conception to production
• Strong portfolio demonstrating impact through deployed models and data-driven solutions
• Experience working with large-scale datasets and distributed computing environments

Technical Skills

• Expert proficiency in Python or R for data analysis and machine learning
• Strong knowledge of machine learning frameworks (scikit-learn, TensorFlow, PyTorch, XGBoost, etc.)
• Advanced SQL skills and experience with various database systems (PostgreSQL, MySQL, NoSQL)
• Experience with big data technologies (Spark, Hadoop, Hive) and cloud platforms (AWS, GCP, or Azure)
• Proficiency in data visualization tools (Matplotlib, Seaborn, Plotly, Tableau, or Power BI)

Domain Knowledge

• Deep understanding of machine learning algorithms including supervised and unsupervised learning techniques
• Expertise in feature engineering, model selection, and hyperparameter optimization
• Knowledge of deep learning architectures and applications (CNNs, RNNs, Transformers)
• Experience with natural language processing, computer vision, or time series analysis (depending on role focus)
• Understanding of model deployment, monitoring, and MLOps best practices

Preferred Qualifications

• Experience with real-time data processing and streaming analytics
• Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience with AutoML platforms and model optimization techniques