
Data Scientist + ML Engineer
2 weeks ago
Roles & Responsibilities:
- Collect, preprocess, and analyze large structured and unstructured datasets.
- Develop, train, and optimize machine learning and deep learning models.
- Build predictive models for classification, regression, recommendation, and NLP/vision tasks.
- Design and implement scalable ML pipelines and deploy them into production environments.
- Conduct feature engineering, model selection, hyperparameter tuning, and validation.
- Monitor model performance, detect drift, and improve accuracy over time.
- Collaborate with product, engineering, and business teams to translate business problems into data-driven solutions.
- Document methodologies, maintain reproducibility, and ensure ethical AI practices.
- Work with big data tools (Spark, Hadoop) and cloud ML services (AWS Sagemaker, GCP AI, Azure ML).
- Stay updated with advancements in AI/ML and contribute to innovation initiatives.
Requirements:
- Bachelors/Master's/PhD in Computer Science, Data Science, Statistics, or related field.
- 5+ years of proven experience in Data Science & Machine Learning.
- Strong coding skills in Python (pandas, numpy, scikit-learn, TensorFlow, PyTorch).
- Solid understanding of statistical modeling, probability, and linear algebra.
- Hands-on with data visualization tools (Tableau, Power BI, matplotlib, seaborn).
- Experience in deploying ML models in production (Docker, Kubernetes, APIs).
- Knowledge of MLOps best practices and cloud AI platforms.
- Strong analytical mindset, critical thinking, and communication skills.
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