Profile : Data Science AnalystLocation : WFO / WFH (Anywhere)Job Description : How you will contribute : – Define requirements for analysis in a given business area and perform detailed analysis and identify trends defined in the requirements- Identify patterns and help the business react to changing business conditions- Perform root-cause analysis and interpret data- Work with large amounts of data such as facts, figures, and mathematics/formulas and undertake analytical activities and delivers analysis outputs in accordance with customer needs and conforming to established standards- Understand and be involved with aspects of the data science process- As the investigator on the data science team, you will apply your knowledge of languages and pull data out of SQL databases, using Tableau/Power BI type tools, and producing basic data visualisations and reporting dashboards- Collaborate with cross-functional teams to gather and understand data requirements for various projects. Clean, pre-process, and transform raw data into usable formats for analysis.- Develop and implement statistical models and algorithms to extract insights from data.- Create and maintain dashboards and reports to track key performance metrics and trends.- Conduct exploratory data analysis to identify patterns, anomalies, and potential areas for improvement.- Assist in designing and conducting A/B tests and experiments to support data-driven decision-making.- Stay up-to-date with industry trends and best practices in data analysis and machine learning.- Document and communicate findings, insights, and recommendations to team members and stakeholders.- Collaborate with senior data scientists to refine and enhance analytical methodologies.- Continuously improve data quality and reliability by identifying and addressing data issues.- Support data-driven decision-making by providing actionable insights and recommendations.What you will bring : – Knowledge of Microsoft Excel, Power BI, SQL,R, Python, SAAS software.- Moderate knowledge in Math and statistical skills, strong business acumen, moderate computer science/coding skills.- Experience with at least one of the data manipulation tools such as Python, R, JAVA, is a must have- Gen AI/ Machine Learning/ Artificial Intelligence, Expertise in Coding, Supervised and Unsupervised Techniques – active learning, transfer learning, neural models, decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models, map reduce techniques, Random Forest, Gradient Boosting, Deep Learning, Text Mining Algorithms- Develop key performance indicators and create visualisations of the data.- Utilise business intelligence and analytics tool. (ref: hirist.com,