Interesting Job Opportunity: Carelon - Senior Data Scientist

Carelon Global Solutions India; Gurugram District; On-site; INR 350,000 - 550,000; Full time

Job summary

Carelon Global Solutions India seeks a Senior Data Scientist with 5+ years in data science, ML, NLP, and healthcare analytics. You will design and deploy models, build pipelines, and collaborate with cross-functional teams on US healthcare data and systems.

Ideal candidates have deep ML/NLP expertise, experience with TensorFlow, PyTorch, Hugging Face, and cloud platforms, and can work independently in a fast-paced environment.

Qualifications

• 5+ years in data science, analytics, or related fields.
• Hands-on NLP, ML, and CV with large-scale data.
• Experience with Python, ML frameworks, and cloud platforms.
• Healthcare domain knowledge and regulatory awareness.

Responsibilities

• Build and deploy ML models for healthcare data.
• Develop data pipelines and MLOps practices.
• Collaborate with AI/ML teams and product stakeholders.
• Evaluate LLMs and NLP solutions with proper metrics.
• Maintain model documentation and experiments.
• Lead data processing for diverse data types.

Skills

Machine Learning

LLM

NLP

Python

SQL

Hugging Face

TensorFlow

Keras

PyTorch

Spark

Cloud experience

Education

Bachelor's or Master's degree in CS/Math/Stats/Engineering

PhD preferred

Tools

Hugging Face

TensorFlow

Keras

PyTorch

Apache Spark

Cloud platforms (GCP/AWS)

Job description

Job Position

We are currently looking to hire a Senior Data Scientist with strong analytical skills and a background in US Healthcare. The ideal candidate should have : - A minimum of 5+ years of overall experience in Data science or related fields - At least 3 years of hands-on experience in Machine Learning (ML) and Natural Language Processing (NLP) Candidates with proven expertise in healthcare data analytics and a solid understanding of healthcare systems in the US will be preferred

Key Responsibilities

• Demonstrate expertise in programming with a strong background in machine learning and data processing.
• Possess strong analytical skills to interpret complex healthcare datasets and derive actionable insights.
• Collaborate closely with AI/ML engineers, data scientists, and product teams to acquire and process data, debug issues, and enhance ML models.
• Develop and maintain enterprise-grade data pipelines to support state-of-the- art AI/ML models.
• Work with diverse data types including structured, semi-structured, and textual data.
• Communicate effectively and collaborate with cross-functional teams including engineering, product, and customer stakeholders.
• Operate independently with minimal guidance from product managers and architects, demonstrating strong decision-making capabilities.
• Embrace complex problems and deliver intelligence-driven solutions with a focus on innovation and scalability.
• Quickly understand product requirements and adapt to evolving business needs and technical environments.

Technical Responsibilities

• Design and implement statistical and machine learning models (e.g., regression, classification, clustering) using frameworks such as scikit-learn, TensorFlow, and PyTorch.
• Build robust data preprocessing pipelines to handle missing values, outliers, feature scaling, and dimensionality reduction.
• Specialize in Large Language Model (LLM) development, including fine-tuning, prompt engineering, and embedding optimization using frameworks like Hugging Face Transformers.
• Develop and optimize LLM evaluation frameworks using metrics such as ROUGE, BLEU, and custom human-aligned evaluation techniques.
• Apply advanced statistical methods including hypothesis testing, confidence intervals, and experimental design to extract insights from complex datasets.
• Create NLP solutions for text classification, sentiment analysis, and topic modeling using both classical and deep learning approaches.
• Design and execute A/B testing strategies, including sample size determination, metric selection, and statistical analysis (e.g., t-tests, ANOVA).
• Implement comprehensive data visualization strategies using tools like Matplotlib, Seaborn, and Plotly to present insights effectively.
• Maintain detailed documentation of model architectures, experiments, and validation results using tools like MLflow or DVC.
• Research and apply LLM optimization techniques such as quantization, pruning, and knowledge distillation to improve efficiency.
• Stay up to date with the latest advancements in statistical learning, deep learning, and LLM research, with a focus on emerging architectures and training methodologies

Qualifications

• Bachelors or masters degree in computer science, Mathematics or Statistics, Computational linguistics, Engineering, or a related field. Ph.D. preferred.

Experience

• 5+ years of overall professional experience in data science, analytics, or related fields.
• 3+ years of hands-on experience working with large-scale structured and unstructured data to develop data-driven insights and solutions using Machine Learning (ML), Natural Language Processing (NLP), and Computer Vision.
• Proven 3+ years of experience with core technologies including Python (mandatory), SQL, Hugging Face, TensorFlow, Keras, PyTorch, and Apache Spark.
• 3+ years of experience in developing NLP models, with a strong focus on transformer-based architectures.
• 2+ years of experience implementing information retrieval systems at scale, including both keyword-based and semantic search using embeddings.
• Hands-on experience with cloud platforms such as Google Cloud Platform (GCP) and Amazon Web Services (AWS).
• Strong expertise in Large Language Model (LLMs) and Generative AI (GAI), including model development, fine-tuning, and optimization.
• Demonstrated ability to work independently with minimal supervision and exercise sound judgment in technical and business decision-making.
• In-depth experience with LLMs (both extractive and generative), including prompt engineering, fine-tuning, and familiarity with open-source ecosystems.
• Experience in prompt development and optimization for NLP applications.
• Strategic thinker with a blend of technical expertise and business acumen, capable of solving complex problems and influencing outcomes.
• Proficient in creating analytical reports, projections, models, and presentations to support business objectives.
• Excellent written and verbal communication skills, with strong stakeholder management capabilities.
• Prior experience in the healthcare industry, with an understanding of domain-specific data and regulatory considerations.

Skills & Competencies

• Must have : Machine Learning, LLM, NLP, Python, SQL, Hugging Face, TensorFlow & Keras.
• Good to have : PyTorch, Spark & any cloud exp.

(ref:hirist.tech)