Job Description Summary

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

Data Analysis & Insights:

• 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

Business Analytics:

• Help generate business performance reports dashboards and metrics to track KPIs
• Support business teams with datadriven recommendations to enhance operational efficiency
• Contribute to decisionmaking processes through analytical insights into business operations

Collaboration & Learning:

• Work closely with crossfunctional teams (e.g. Sales Finance Services Engineering) to understand business needs and deliver datadriven 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

Documentation & Reporting:

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

Qualifications required:

Education: Bachelors degree in Data Science and Business Analytics or a related field

Technical Skills:

• Knowledge Internship or academic projects related toprogramming 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)

Desired qualifications:

• Strong analytical and problemsolving 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.

Additional Information