Business Analytics Internship

4 weeks ago

Bengaluru, Karnataka, India DataZymes Analytics Full time

About the internship:

Selected intern's day-to-day responsibilities include:

1. Gaining comprehensive knowledge of the Life Sciences and Healthcare domain.

2. Completing the Analytics Bootcamp by DataZymes, including all assignments, assessments, and projects.

3. Undergoing training on business and client processes for report generation, ad hoc analysis, and process documentation.

4. Collaborating in designing and implementing data visualization dashboards and reports to track KPIs, monitor business metrics, and communicate findings.

5. Supporting data management and quality assurance efforts to maintain data integrity, accuracy, and regulatory compliance.

6. Assisting in developing and maintaining predictive models, machine learning algorithms, and statistical techniques for sales forecasting, pricing optimization, and demand forecasting.

7. Staying informed on industry trends, regulatory changes, and emerging technologies in the pharmaceutical sector to drive continuous improvement and inform business strategies.

>

Only those candidates can apply who:


1. are available for full time (in-office) internship


2. can start the internship between 17th May'24 and 21st Jun'24


3. are available for duration of 6 months


4. have relevant skills and interests


* Freshers looking for jobs may also apply

Stipend:

INR ₹ 15,000 /month

Deadline:

:59:59

Other perks:

Certificate, Letter of recommendation, Flexible work hours, Informal dress code, Job offer

Skills required:

Python, SQL, Statistics and Power BI

About Company:

DataZymes, founded in 2016, has its offices in the US and India. DataZymes (DZ) is a boutique data science company focused on combining digital technologies, data science, and deep domain expertise to make business processes in life sciences organizations more intelligent and adaptive. We differentiate by enabling clients access to digital enabled analytical solutions that allow them to scale the level of analytics and achieve non-linear growth.

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