Data scientist

Primary Skills: Python, Machine Learning, SQL, Data Analysis, Statistical Modeling Location: Remote

As a Data Scientist, you will be responsible for designing, developing, and deploying machine learning models, building data pipelines, and performing exploratory data analysis on large datasets.

What You Get to Do:

• Design, develop, and deploy machine learning models for predictive analytics.
• Perform exploratory data analysis (EDA) on large, complex datasets (1M+ records).
• Build and maintain data pipelines for model training and inference.
• Create clear visualizations and reports to communicate insights to stakeholders.
• Implement MLOps practices for productionizing models (monitoring, retraining).
• Collaborate with engineering teams to integrate models into production systems.
• Stay current with the latest developments in ML/AI and evaluate new techniques.
• Optimize model performance through hyperparameter tuning and algorithm selection.

What You Need to Succeed:

• 4+ years of professional experience in data science with strong Python programming skills (NumPy, Pandas, Scikit-learn).
• Expertise in machine learning frameworks (TensorFlow, PyTorch, Keras) for developing and deploying models.
• Advanced SQL skills for complex querying, optimization, and database management (PostgreSQL, MySQL).
• Experience with end-to-end data pipeline development including:
  • Data ingestion from multiple sources (APIs, databases, .
  • Data cleaning/wrangling (handling missing values, outliers, imbalanced data).
  • Feature engineering and selection.
• Cloud platform experience (AWS SageMaker, S3, Redshift, or equivalent GCP/Azure services).
• Strong mathematical foundation in:
  • Probability and statistics (distributions, hypothesis testing).
  • Linear algebra (matrix operations, eigenvectors).
  • Calculus (gradients, optimization).

Good to Have:

• Experience with NLP techniques (BERT, transformers, text classification).
• Computer vision experience (OpenCV, CNN architectures).
• Experience with containerization (Docker) and model serving (FastAPI, Flask).
• Knowledge of experimental design and A/B testing methodologies.
• Published research or contributions to open-source ML projects.

Education Qualification:

• Master s or PhD preferred in Computer Science, Statistics, Applied Mathematics, or related quantitative field.
• Bachelor s degree acceptable with exceptional experience and proven track record.