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Responsibilities
Gather, refine, preprocess, and analyze datasets for practical data projects.
Use Python to conduct exploratory data analysis in business contexts, including banking and finance risk analytics.
Apply machine learning, data mining, and statistical techniques to identify patterns and evaluate hypotheses.
Collaborate with data science colleagues and stakeholders to develop analytical models and machine learning pipelines.
Explore business data and assess strategies using methods such as T-tests.
Use analytical tools, including Tableau, to examine and present data.
Prepare reports and presentations that explain analytical methods and findings.
Qualifications
You are currently pursuing a degree and demonstrate commitment to continuous learning and professional growth.
You have strong problem-solving and critical-thinking abilities.
You communicate effectively and work well with others.
You can work independently in a remote setting.
Experience with Python-based exploratory data analysis would strengthen your application.
Familiarity with machine learning, data mining, or statistical testing would be useful.
Exposure to Tableau, data visualization, or analytical reporting would be an advantage.
Work Environment
The internship is remote.
The listing associates the role with London, England, United Kingdom; it does not provide further location or work-eligibility details.
You will collaborate with a data science team and internal stakeholders.
The listing does not specify working hours or travel requirements.
Benefits & Perks
The internship is unpaid.
The program offers practical experience through real-world data projects.
You can develop analytical skills in data preprocessing, visualization, modeling, and reporting.
The role provides opportunities to learn about business applications across finance, commerce, and procurement.