Profile : Data Science Analyst

Location : 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.