Data Scientist

About the Role and Company

Crescendo Global Leadership Hiring India specializes in senior and executive recruitment, striving to provide a supportive and inclusive experience for both candidates and employers without discrimination.

Technical Responsibilities and Skills

• Expertise in Python and major machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, and PyTorch.
• Understanding and practical application of machine learning techniques including classification, regression, survival analysis, feature engineering, model tuning, and model explainability.
• Experience with Natural Language Processing and Deep Learning methods applicable to both structured and unstructured datasets, including text classification and document analytics.
• Hands-on knowledge of Generative AI and Large Language Models encompassing prompt engineering, embeddings, retrieval-augmented generation, vector databases, and model assessment.
• Familiarity with MLOps practices and model lifecycle management, including deployment, monitoring, drift detection, retraining, and working with tools like MLflow, Airflow, Docker, Kubernetes, or cloud-native ML solutions.
• Strong skills in SQL and data manipulation capable of handling large-scale structured and unstructured datasets.
• Understanding of relational databases, data modeling, and foundational data architecture principles.
• Capability to apply structured problem-solving and analytical thinking to design scalable, practical data science solutions.
• Preferred exposure to group insurance, healthcare, disability insurance, or claims analytics along with knowledge of insurance data structures such as policies, coverages, claims, and insured members.
• Added advantage for those with insights into healthcare or disability insurance workflows like claims adjudication, utilization management, or provider analytics.
• Experience in working collaboratively with cross-functional teams and engaging stakeholders within project settings.
• Proficiency in communicating complex analytical results clearly across technical and non-technical audiences.

Candidate Profile and Qualifications

• Bachelor’s or Master’s degree in computer science, engineering, data science, mathematics, or related analytics disciplines.
• Over six years of practical experience developing data science, machine learning, or AI solutions that drive business value, preferably in healthcare, insurance, disability claims, or similarly regulated sectors.
• Ability to engineer practical data science applications utilizing both structured and unstructured data.
• Exemplary analytical and problem-solving capabilities.
• Excellent written and oral communication skills.
• Adaptability to fast-changing environments with a strong sense of ownership of challenging analytical assignments.
• Cross-cultural awareness and ability to collaborate effectively with global clients.