Data Scientist

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About the Opportunity:

Omnihire is seeking a Data Scientist to join a leading AI-driven data‐solutions company. As part of the Data Consulting team, you’ll collaborate with scientists, IT, and engineering to solve high-impact problems and deliver actionable insights.

Key Responsibilities:

• Analyze large, structured and unstructured datasets (SQL, Hadoop/Spark) to extract business-critical insights
• Build and validate statistical models (regression, classification, time-series, segmentation) and machine-learning algorithms (Random Forest, Boosting, SVM, KNN)
• Develop deep-learning solutions (CNN, RNN, LSTM, transfer learning) and apply NLP techniques (tokenization, stemming/lemmatization, NER, LSA)
• Write production-quality code in Python and/or R using libraries (scikit-learn, TensorFlow/PyTorch, pandas, NumPy, NLTK/spaCy)
• Collaborate with cross-functional teams to scope requirements, propose analytics solutions, and present findings via clear visualizations (Power BI, Matplotlib)
• Own end-to-end ML pipelines: data ingestion → preprocessing → feature engineering → model training → evaluation → deployment
• Contribute to solution proposals and maintain documentation for data schemas, model architectures, and experiment tracking (Git, MLflow)

Required Qualifications:

• Bachelor’s or Master’s in Computer Science, Statistics, Mathematics, Data Science, or a related field
• 2–5 years of hands-on experience as a Data Scientist (or similar) in a data-driven environment
• Proficiency in Python and/or R for statistical modeling and ML
• Strong SQL skills and familiarity with Big Data platforms (e.g., Hadoop, Apache Spark)
• Demonstrated experience building, validating, and deploying ML/DL models in production or staging
• Excellent problem-solving skills, attention to detail, and ability to communicate technical concepts clearly
• Self-starter who thrives in a collaborative, Agile environment

Nice-to-Have:

• Active GitHub/Kaggle portfolio showcasing personal projects or contributions
• Exposure to cloud-based ML services (Azure ML Studio, AWS SageMaker) and containerization (Docker)
• Familiarity with advanced NLP frameworks (e.g., Hugging Face Transformers) or production monitoring tools (Azure Monitor, Prometheus)

Why Join?

• Work on high-impact AI/ML projects that drive real business value
• Rapid skill development with exposure to cutting-edge technologies
• Collaborative, Agile culture with mentorship from senior data scientists
• Competitive compensation package and comprehensive benefits