Data Scientist

Overview

Job Purpose

The Data Scientist will be responsible for building data-driven solutions, predictive models, and AI/ML applications that support business growth, customer experience, and operational efficiency. The role requires strong analytical capabilities, problem-solving skills, and the ability to work collaboratively across business and technology teams. The incumbent will work on advanced analytics, machine learning, automation, and AI initiatives to derive actionable insights and scalable solutions.

Key Responsibilities

Financial

· Support business growth through data-driven insights and predictive analytics.

· Optimize operational efficiency through automation and analytical solutions.

· Contribute towards improving business KPIs through AI/ML initiatives.

Customer

· Analyze customer behaviour, engagement, and usage trends to derive actionable insights.

· Build predictive models for customer engagement, retention, and experience enhancement.

· Support personalization and recommendation initiatives using AI/ML techniques.

· Develop dashboards and analytical reports for business stakeholders and leadership teams.

Technology & Strategic Support

· Design, develop, validate, and deploy machine learning models and statistical solutions.

· Perform data extraction, cleaning, preprocessing, and exploratory data analysis (EDA).

· Develop scalable analytical frameworks and automated workflows.

· Work closely with engineering, product, and business teams for model deployment and monitoring.

· Build solutions leveraging NLP, Deep Learning, Generative AI, and advanced analytics where applicable.

· Ensure proper documentation of models, datasets, processes, and analytical methodologies.

· Stay updated with emerging technologies and trends in AI, Machine Learning, and Data Science.

· Support strategic AI and digital transformation initiatives as required.

Qualifications:

· Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related quantitative disciplines.

· Minimum 5+ years of experience in Data Science, Machine Learning, or Analytics roles.

· Experience in Healthcare, Wellness, HR Tech, SaaS, or Product-based organizations preferred.

· Strong hands-on experience in Python, SQL, and Machine Learning algorithms.

· Experience working with ML frameworks such as Scikit-learn, TensorFlow, PyTorch, or similar technologies.

· Exposure to cloud platforms such as AWS, Azure, or GCP preferred.

· Experience with NLP, Deep Learning, MLOps, or Generative AI will be an added advantage.

Knowledge, Skills & Abilities (KSAs)

Knowledge (What the person should know)

· Strong understanding of Machine Learning, Statistical Modeling, and Predictive Analytics.

· Knowledge of data preprocessing, feature engineering, and model evaluation techniques.

· Familiarity with cloud environments, APIs, and deployment workflows.

· Understanding of data visualization and business intelligence concepts.

· Awareness of emerging AI and Generative AI technologies.

Skills (What the person should be able to do)

· Strong analytical and problem-solving skills.

· Excellent programming skills in Python and SQL.

· Ability to develop, test, and optimize ML models.

· Strong communication and presentation skills.

· Ability to translate business requirements into analytical solutions.

· Strong stakeholder collaboration and cross-functional working ability.

Abilities (Capacity to perform based on attributes)

· Ability to work independently and drive analytical initiatives end-to-end.

· Ability to handle large datasets and derive meaningful insights.

· Ability to adapt quickly to changing technologies and business priorities.

· Ability to work in a fast-paced and innovation-driven environment.

· Ability to collaborate effectively across business and technology teams.