Data Scientist

Masters degree in Computer Science, Statistics, Mathematics, or a related field. 7+ years of experience in data science and machine learning with a strong focus on model development and deployment. Expert-level knowledge of statistics, including probability theory, hypothesis testing, and statistical inference. In-depth knowledge of machine learning algorithms, including linear regression, logistic regression, decision trees, random forests, xgboost, and ensemble learning. Strong programming skills in Python and proficiency in data science libraries like pandas, scikit-learn, numpy, Pytorch/Keras, and TensorFlow. Experience with cloud computing platforms, particularly Google Cloud Platform (GCP). Excellent data visualization skills using tools like matplotlib, seaborn, or Tableau. Strong communication and presentation skills, both written and verbal. Experience with Natural Language Processing (NLP) and Computer Vision (CV) techniques. Knowledge of DevOps methodologies and practices for continuous integration/continuous delivery (CI/CD). Experience with data warehousing and data lakes solutions like BigQuery or Snowflake. Familiarity with real-time data processing and streaming analytics. Passion for learning and staying at the forefront of data science and machine learning advancements. Good knowledge on software configuration management systems Strong business acumen, strategy and cross-industry thought leadership Awareness of latest technologies and Industry trends Logical thinking and problem solving skills along with an ability to collaborate Two or three industry domain knowledge Understanding of the financial processes for various types of projects and the various pricing models available Client Interfacing skills Knowledge of SDLC and agile methodologies Project and Team management