entry-level data scientist

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You’re an entry-level data scientist and you are asked in an interview to describe your skill set. What is the best way to answer that question? Smith Hanley offers up an interesting approach.

 

Software

The foundation of my skill set for doing data science starts with my programming skills. I have used both R and Python in my academic coursework and feel I am very strong in Python with experience in Numpy and Panda Libraries and better than beginner in R. I have academic and internship experience with SQL and have used it with very large databases.

Working with Data

I have more than average experience with cleaning data or data wrangling. I know a large percentage of my entry-level data scientist job will be in this area, and I know how to recognize corrupt or wrong data and how to correct or delete the offending information.

Statistics and Machine Learning

I can explain and have used applications including the null hypothesis, P-value, maximum likelihood estimators and confidence intervals. I understand their implication and their application for designing experiments. I have some academic experience with logistic regression for doing predictive analytics and I have been exposed to random forests. I know Statistics is important for analyzing the data and extracting the most relevant information. I have taken a number of online courses in Machine Learning and did a number of predictive analytics projects in my coursework. I can explain the use of K-nearest neighbors, random forests and ensemble methods. I can use them in Python and some of them in R.

Data Visualization

I believe my data visualization skills set me apart from most entry-level data scientists. I am able to communicate my analysis and results to technical and non-technical audiences. I am comfortable speaking to groups and I am confident I can present results in an interesting fashion. I consider myself an expert with ggplot.

Conclusion

I believe I have all the building blocks to be a contributor to your team. For what I lack in experience, I make up for in energy and enthusiasm for your firm and for the work I will do as an entry-level data scientist. I hope you will give me the opportunity.

Perhaps your skill set doesn’t exactly match the list above.  Your strengths are not as strong in data visualization but better in programming or applied stat. Making a case for the skills you do have is essential in the entry-level data scientist interview process.

We’d love to help you find an entry-level data scientist job and put your skills to use. Contact the Smith Hanley Associates’ Data Science and Analytics Recruiters:

Paul Chatlos, [email protected]

Nancy Darian, [email protected]

Rachel Pereira, [email protected]


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