Early Career Trainee - Data Science and Business Analytics

Job Description Summary

As an Early Career Trainee in Data Science and Business Analytics, you will play an integral role within our Global Sales Operations team, gain hands-on experience in application of various methodologies used in the analytical and data-driven techniques to optimize operations, and enhance decision-making processes. This opportunity is ideal for recent graduates or individuals with minimal professional experience who are passionate about using data science and analytics to drive business outcomes in a global sales environment. You will collaborate with senior team members, cross-functional teams and contribute to ongoing projects.

Job Description

Data Collection & Preparation:

• Assist in gathering and preparing data from multiple sources for analysis
• Clean, transform, and preprocess raw data to ensure accuracy and consistency
• Explore datasets to identify trends, patterns, and potential anomalies

• Support the team in performing exploratory data analysis (EDA) and hypothesis testing
• Utilize statistical and machine learning techniques to uncover insights from data
• Generate reports summarizing findings, with clear visualizations and actionable insights and recommendations

• Assist in building and validating predictive models using statistical and machine learning methods
• Learn and apply relevant algorithms (e.g., regression, classification, clustering) to solve business problems

• Help generate business performance reports, dashboards, and metrics to track KPIs
• Support business teams with data-driven recommendations to enhance operational efficiency
• Contribute to decision-making processes through analytical insights into business operations

• Work closely with cross-functional teams (e.g., Sales, Finance, Services, Engineering) to understand business needs and deliver data-driven solutions
• Participate in training sessions and mentorship to improve technical skills in data science and analytics tools
• Stay up to date with industry trends, new technologies, and best practices in data science

• Document workflows, business requirements, methodologies, and project outcomes
• Create presentations and reports to communicate findings effectively to non-technical stakeholders
• Assist in preparing and presenting regular updates on project progress.

• Knowledge, Internship or academic projects related to programming languages like Python, VB or R
• Basic understanding of machine learning techniques (e.g., regression, clustering, classification)
• Basic understanding of statistical analysis, techniques and RDBMS concepts
• Knowledge with data analysis tools (e.g., MS Excel, SQL - MySQL, PostgreSQL)
• Experience, Internship or academic projects related to with data visualization tools (e.g., Tableau, Power BI)

• Strong analytical and problem-solving abilities.
• Excellent communication skills, with the ability to explain complex concepts in simple terms.
• Ability to work independently and as part of a team.
• Eagerness to learn and adapt to new tools, technologies, and methodologies.