Senior Data Scientist

Role: Senior Data Scientist

Experience: 10+ Years of Experience

Location: Remote

Employment Type: W2 Full-Time

Key Responsibilities

• Design, develop, and deploy advanced machine learning and statistical models to solve complex business problems.
• Conduct exploratory data analysis (EDA), feature engineering, and data preprocessing for large-scale structured and unstructured datasets.
• Collaborate with data engineers to build scalable data pipelines supporting model training and real-time inference.
• Leverage modern ML frameworks (TensorFlow, PyTorch, Scikit-learn, XGBoost) to create predictive and prescriptive models.
• Partner with product managers and stakeholders to define analytical use cases and translate business needs into data-driven solutions.
• Build and maintain MLOps pipelines for training, testing, deployment, and monitoring using tools such as MLflow, SageMaker, Vertex AI, or Kubeflow.
• Communicate insights and results clearly through visualizations, dashboards, and storytelling for technical and non-technical stakeholders.
• Ensure compliance with data governance, privacy, and responsible AI practices (bias detection, fairness, explainability).
• Mentor junior data scientists and contribute to knowledge sharing, best practices, and research within the organization.

Required Qualifications

• 8+ years of hands-on experience as a Data Scientist or Machine Learning Engineer.
• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow) and SQL.
• Expertise in statistical analysis, probability, hypothesis testing, and optimization methods.
• Experience in building and deploying ML models in production at scale.
• Strong background in data wrangling, feature engineering, and model evaluation techniques (A/B testing, cross-validation, ROC, precision/recall).
• Familiarity with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML).
• Experience with data visualization tools (Tableau, Power BI, Matplotlib, Seaborn, Plotly).
• Bachelor’s/Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field (PhD preferred).

Preferred Skills

• Experience with natural language processing (NLP), generative AI, or computer vision.
• Knowledge of big data technologies (Apache Spark, Hadoop, Kafka).
• Exposure to MLOps practices and tools (MLflow, TFX, Airflow).
• Familiarity with containerization & orchestration (Docker, Kubernetes) for ML workflows.
• Understanding of deep learning architectures (CNNs, RNNs, Transformers, LLMs).
• Experience working in Agile/Scrum environments.
• Relevant certifications (AWS ML Specialty, TensorFlow Developer, GCP Professional Data Scientist).