Data Scientist - Intern

Responsibilities include, but not limited to: 

• Collaborate with business stakeholders across finance, sales, business units, HR, and/or legal to understand their needs and translate them into data science projects and solutions. 

• Design, develop, and implement predictive models, machine learning models, statistical analysis, and data mining techniques to address business challenges. 

• Analyze large and complex datasets, identifying trends, patterns, and anomalies to extract valuable and actionable insights. 

• Build and deploy data visualization dashboards and reports to effectively communicate insights to business stakeholders across different levels. 

• Research and explore new data science techniques, including generative AI and large language models, to enhance business processes and decision-making. 

• Contribute to data governance and infrastructure: Help maintain and improve our data infrastructure, ensuring data quality and integrity. 

Qualifications: 

• Completed a bachelor’s degree and working towards a master’s degree or PhD. 

• Strong analytical and problem-solving skills with the ability to translate data into actionable insights. 

• Strong foundation in statistical modeling, machine learning algorithms, and data mining techniques. 

• Working knowledge of machine learning algorithms and techniques, including supervised and unsupervised learning. 

• Proficiency in Python and R programming languages (Python is preferred), including relevant libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch. 

• Ability to work with large datasets and cloud platforms (e.g., Google Cloud, AWS, Azure). 

• Strong understanding of data visualization tools and techniques. 

• Ability to apply generative AI and large language models (LLMs) within business contexts. 

• Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques. 

• Experience with SQL databases and data manipulation tools. Proven experience combining data sets across business functions to achieve desired project objectives 

• Desire to work in a dynamic and fast paced environment. 

• Excellent communication and presentation skills, with the ability to effectively convey complex data insights to non-technical audiences. 

 Education: 

• Master's degree in Statistics, Data Science, Computer Science, or a related field.