Data Scientist - Gen AI - NLP

Job Description

We are actively seeking a talented and results-driven Data Scientist to join our team and take on a leadership role in driving business outcomes through the power of data analytics and insights. - Your contributions will be instrumental in making data-informed decisions, identifying growth opportunities, and propelling our organization to new levels of success. - Doctorate/Master's/bachelor's degree in data science, Statistics, Computer Science, Mathematics, Economics, commerce or a related field. - Minimum of 4 years of experience working as a Data Scientist or in a similar analytical role, with experience leading data science projects and teams. Experience in Healthcare domain with exposure to clinical operations, financial, risk rating, fraud, digital, sales and marketing, and wellness, e-commerce or the ed tech industry is a plus. - Proven ability to lead and mentor a team of data scientists, fostering an innovative environment. Strong decision-making and problem-solving skills to guide strategic initiatives. - Expertise in programming languages such as Python and R, and proficiency with data manipulation, analysis, and visualization libraries (e.g., pandas, NumPy, Matplotlib, seaborn). - Deep understanding of machine learning algorithms, model evaluation, and feature engineering. Experience with frameworks like scikit-learn, TensorFlow, or Pytorch. - Strong expertise in statistical modelling techniques such as regression, clustering, time series analysis, and hypothesis testing. - Experience of building & deploying machine learning models in cloud environment: Microsoft Azure preferred (Databricks, Synapse, Data Factory, etc.) - Knowledge of the MLOps process and AI governance - Ability to understand business objectives, market dynamics, and strategic priorities. Demonstrated experience translating data insights into tangible business outcomes and driving data-informed decision-making. - Excellent verbal and written communication skills - Proven experience leading data science projects, managing timelines, and delivering results within deadlines. - Strong collaboration skills with the ability to work effectively in cross-functional teams, build relationships, and foster a culture of knowledge sharing and continuous learning.