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 practicesOptimize model performance through feature engineering, hyperparameter tuning, and algorithm selectionImplement MLOps practices including model versioning, monitoring, and continuous improvementStay current with the latest developments in data science, machine learning, and AI technologiesCross-functional Collaboration
Partner with product managers, engineers, and business stakeholders to identify opportunities for data-driven solutionsCollaborate with data engineering teams to ensure data quality, accessibility, and infrastructure requirements are metWork with software engineers to integrate models into production systems and applicationsPresent findings and recommendations to senior leadership and key stakeholdersRequired Qualifications
Experience
7+ years of professional experience in data science, machine learning, or related analytical rolesProven track record of successfully delivering end-to-end data science projects from conception to productionStrong portfolio demonstrating impact through deployed models and data-driven solutionsExperience working with large-scale datasets and distributed computing environmentsTechnical Skills
Expert proficiency in Python or R for data analysis and machine learningStrong 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 techniquesExpertise in feature engineering, model selection, and hyperparameter optimizationKnowledge 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 practicesPreferred Qualifications
Experience with real-time data processing and streaming analyticsFamiliarity with containerization (Docker, Kubernetes) and CI / CD pipelinesExperience with AutoML platforms and model optimization techniques