Data Scientist with Machine Learning specialization:

Job Title: Senior Data Scientist – Machine Learning Specialist (Remote)

Location: Remote

Experience: 7+ Years

Employment Type: Full-time

About The Role

We are seeking a highly experienced Senior Data Scientist with a specialization in Machine Learning to join our remote team. The ideal candidate has a strong background in data

science, statistics, and end-to-end machine learning model development and deployment. You will work closely with cross-functional teams to build and scale ML solutions that solve complex

business problems.

Key Responsibilities

• Lead the design, development, and deployment of scalable machine learning models for business-critical applications.
• Perform advanced data analysis, feature engineering, and algorithm selection for classification, regression, clustering, NLP, or time-series problems.
• Collaborate with data engineers, software engineers, and product managers to integrate models into production systems.
• Conduct rigorous experimentation and A/B testing to evaluate model performance.
• Optimize ML pipelines for performance, scalability, and maintainability in cloud or hybrid environments.
• Communicate findings, model outcomes, and actionable insights to both technical and non-technical stakeholders.
• Stay updated with the latest advancements in AI/ML research and apply relevant innovations to business use cases.
• Mentor junior data scientists and contribute to best practices and knowledge sharing.

Required Skills & Qualifications

• 7+ years of professional experience in data science and machine learning.
• Proficiency in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM).
• Strong understanding of supervised and unsupervised learning, deep learning, NLP, and/or time-series forecasting.
• Experience with end-to-end ML model lifecycle, including data preprocessing, model training, evaluation, deployment, and monitoring.
• Proficiency in SQL and working with structured and unstructured datasets.
• Experience with cloud platforms like AWS, GCP, or Azure (e.g., SageMaker, Vertex AI, Azure ML).
• Knowledge of CI/CD pipelines and ML Ops tools (e.g., MLflow, Kubeflow, Airflow, Docker).
• Strong problem-solving skills and ability to translate business needs into technical solutions.
• Excellent verbal and written communication skills.