Job Title - Data Scientist (w/ Python & NLP)
Key Responsibilities:
- Business Translation: Translate business needs into analytics/reporting requirements to support data-driven decisions and provide actionable insights.
- Programming & Tools: Proficient in at least one analytical programming language relevant to data science, with Python preferred. Experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn) and data processing/visualization tools (e.g., SQL, Tableau, Power BI).
- NLP Expertise: Strong knowledge of Natural Language Processing (NLP) and its application in healthcare.
- Advanced Analytics: Expertise in advanced analytical techniques, including descriptive statistics, machine learning, optimization, pattern recognition, and cluster analysis.
- Cloud & ML Platforms: Experience with cloud computing environments (preferably GCP) and Data/ML platforms like Databricks and Spark.
- Machine Learning Lifecycle: Strong understanding of the Machine Learning lifecycle, including feature engineering, training, validation, scaling, deployment, monitoring, and feedback loops.
- Supervised & Unsupervised Learning: Proficiency in supervised and unsupervised machine learning techniques, including classification, forecasting, anomaly detection, and pattern recognition using decision trees, regressions, ensemble methods, and boosting algorithms.
- Leverage Technologies: Utilize ML and LLM technologies to extract insights from complex data sets.
Required Qualifications:
- Education: Master’s degree or PhD in Computer Science, Statistics, Applied Mathematics, or a related field.
- Experience:
- 5-7 years of experience in data science or a similar role.
- Proficient in Python (or R), machine learning libraries, and data processing/visualization tools.
- Strong expertise in NLP.
- Experience with cloud environments like GCP and ML platforms like Databricks and Spark.
- Solid understanding of the entire machine learning lifecycle.
- Proven experience in supervised and unsupervised learning methods.