Data Scientist Internship

Santiago - Chile

Monthly Salary: Not Disclosed

Posted on: 13 hours ago

Vacancies: 1 Vacancy

Job Summary

Data Scientist Internship

Description -

We are looking for a student enrolled as a Civil Engineering focusing in Data Analysis who will support the sales and operations teams by identifying analyzing and automating key processes that drive commercial efficiency and enable datadriven decisionmaking.

Main Responsibilities

Sales process mapping and analysis:
Document current sales workflows identify bottlenecks inefficiencies and opportunities for improvement.
Data collection and preparation:
Extract clean and structure data from different internal sources (CRM ERP commercial reports historical databases etc.).
Development of automated dashboards and reporting:
Build interactive dashboards and automated reports using tools such as Power BI Tableau or equivalent enabling effective KPI tracking for the sales team.
Implementation of automation solutions:
Design and develop automations to reduce manual tasks within the commercial area using tools like Python SQL Power Automate or internal scripting tools.
Statistical modeling and analysis:
Apply data analysis techniques to uncover patterns trends and insights that support commercial planning and forecasting.
Process optimization:
Propose adjustments or redesigns of processes based on data with a focus on efficiency productivity and error reduction.
Technical and operational documentation:
Document methodologies scripts workflows and procedures to ensure operational continuity and knowledge transfer.
Crossfunctional collaboration:
Work alongside the sales IT operations and commercial management teams to ensure proposed solutions align with business needs.

Education and Experience Required:
Enrolled in University.

Job -

Administration

Schedule -

Full time

Shift -

No shift premium (Chile)

Travel -

Relocation -

Equal Opportunity Employer (EEO) -

HP Inc. provides equal employment opportunity to all employees and prospective employees without regard to race color religion sex national origin ancestry citizenship sexual orientation age disability or status as a protected veteran marital status familial status physical or mental disability medical condition pregnancy genetic predisposition or carrier status uniformed service status political affiliation or any other characteristic protected by applicable national federal state and local law(s).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

For more information review HPsEEO Policy or read about your rights as an applicant under the law here: Know Your Rights: Workplace Discrimination is Illegal

Required Experience:

Intern

Data Scientist InternshipDescription -We are looking for a student enrolled as a Civil Engineering focusing in Data Analysis who will support the sales and operations teams by identifying analyzing and automating key processes that drive commercial efficiency and enable datadriven decisionmaking.Mai...

Data Scientist Internship

Description -

Main Responsibilities

Sales process mapping and analysis:
Document current sales workflows identify bottlenecks inefficiencies and opportunities for improvement.
Data collection and preparation:
Extract clean and structure data from different internal sources (CRM ERP commercial reports historical databases etc.).
Development of automated dashboards and reporting:
Build interactive dashboards and automated reports using tools such as Power BI Tableau or equivalent enabling effective KPI tracking for the sales team.
Implementation of automation solutions:
Design and develop automations to reduce manual tasks within the commercial area using tools like Python SQL Power Automate or internal scripting tools.
Statistical modeling and analysis:
Apply data analysis techniques to uncover patterns trends and insights that support commercial planning and forecasting.
Process optimization:
Propose adjustments or redesigns of processes based on data with a focus on efficiency productivity and error reduction.
Technical and operational documentation:
Document methodologies scripts workflows and procedures to ensure operational continuity and knowledge transfer.
Crossfunctional collaboration:
Work alongside the sales IT operations and commercial management teams to ensure proposed solutions align with business needs.