An AI agent that applies to roles like this on employers' own sites. 25 applications free, no card needed.
Posted over 15 days ago, so the role may have closed. Confirm on the employer's page when you apply, or see similar jobs.
Job Description
Location: Remote
- Collect, clean, and preprocess large structured and unstructured datasets.
- Develop, train, validate, and deploy machine learning models for business applications.
- Perform exploratory data analysis (EDA) to identify trends, patterns, and opportunities.
- Design and implement predictive, classification, clustering, and recommendation models.
- Collaborate with business stakeholders to understand requirements and translate them into analytical solutions.
- Build end-to-end data science pipelines and automate model training and monitoring processes.
- Evaluate model performance using appropriate metrics and optimize models for accuracy and scalability.
- Communicate findings and recommendations through visualizations, dashboards, and presentations.
- Work closely with Data Engineers, Software Engineers, and Product teams to deploy solutions into production.
- Stay updated with the latest advancements in AI, Machine Learning, and Data Science.
- Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
- 8+ years of experience in Data Science and Machine Learning
- Strong knowledge of statistical analysis and machine learning algorithms.
- Experience with Python and data science libraries such as:
- Pandas
- NumPy
- Scikit-learn
- TensorFlow/Keras
- PyTorch
- Strong SQL skills and experience working with relational databases.
- Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/Seaborn.
- Understanding of model deployment and MLOps practices.
- Experience working with cloud platforms such as Azure, AWS, or Google Cloud Platform.
- Experience with Generative AI and Large Language Models (LLMs).
- Knowledge of NLP, Computer Vision, or Deep Learning frameworks.
- Hands-on experience with Docker, Kubernetes, and CI/CD pipelines.
- Familiarity with Spark, Databricks, or distributed computing frameworks.
- Relevant certifications in Data Science, Machine Learning, Azure AI, AWS ML, or Google Cloud Platform AI.
- Python
- SQL
- R (Optional)
- Machine Learning:
- Supervised Learning
- Unsupervised Learning
- Time Series Forecasting
- Deep Learning
- NLP
- Feature Engineering
- Model Evaluation & Optimization
- Jupyter Notebook
- Git/GitHub
- Azure ML / AWS SageMaker / Vertex AI
- Databricks
- Docker
- Power BI / Tableau
- Analytical Thinking
- Problem Solving
- Business Acumen
- Communication & Presentation Skills
- Stakeholder Management
- Team Collaboration
- Innovation Mindset
Skills
Advanced AnalyticsData VisualizationPythonData AnalysisData ScienceDeep LearningMachine LearningStatistical ModelingVisualizationData ScientistLarge Language ModelsAnalyticsAiGoogle CloudMlSqlLlmsGenerative AiModel EvaluationPytorchTensorflowKerasScikit-learnNumpyPandasNlpComputer VisionMlopsSagemakerVertex AiDatabricksModel DeploymentModel TrainingFeature EngineeringIf a job posting appears fraudulent, asks for payment, contains misleading information, or violates our guidelines, please report it immediately. Our team will review it promptly, Jobaaj does not charge any fee from the applicants.
About Company
Similar Jobs
View allNew Data Science Analytics & Machine Learning roles in US.
One email a day. Unsubscribe any time.

