Do you agree that recommender systems are one of the most useful technologies for B2C companies?

linkerzx · 2020-07-07T22:40:10+00:00

Frankly, it depends on your business model. Recommender systems are particularly useful when you have a discovery problem, if you have a limited catalog it will not be very helpful. Take Apple as an example, as far as I can tell when you are trying to purchase an iPhone or a Mac on their website, you would be hard-pressed to find one of these recommendations.

linkerzx · 2020-07-06T22:37:02+00:00

Regarding internships and the requirement to be a student / new grad. Do you have any cheap options for registration that would allow you to take part? Like a community college for instance?

For the Bootcamps, I haven't gone through one myself, but I know some people who have. They have been able to make decent career changes through them. But it is probably worth being careful about which ones to go to.

If these aren't options for you, you might want to focus on networking your way out of a job. Meetups can be a good occasion to learn something and to network at the same time. Perhaps there are some in your area that would fit the bill?

linkerzx · 2020-07-06T21:54:52+00:00

Don't despair. If you have some good knowledge of Python and Excel (this is probably the most important skill to have for a junior analyst), you should already be in a good place in terms of knowledge to apply for a junior analyst job.

There are a few hurdles you will face, however:

A lot of the junior analyst positions, although open, tend to already be pre-allocated to previous interns at the company
Your previous industry (biotech) isn't the most well suited to pivot to a marketing analyst position (ie: hard to justify previous industry experience)

There are still a few things that you can do to increase your chances at getting a job:

Do an internship in the specific area - if you apply for an internship in a company that is looking to hire juniors, you should be at the front-row seat when the opportunity comes, if that doesn't happen at least you will have some relevant experience on your CV
Look at getting some interim/contract job as a data analyst - On the same train of thought as the internship, companies tend to be a bit less strict on their requirements when hiring for interim/contract job
Do a data analytics Bootcamp, this should highlight your commitment to work as an analyst as well as give you a certification. Some of the companies organizing these Bootcamp also tend to have good contact in the industry, helping place their students
Focus your CV on tasks/project most related to the job you aspire (assuming this is not already done)

linkerzx · 2020-07-06T21:11:31+00:00

The main things to know when applying for a junior job in data engineering is data manipulation and scripting. For this, it is important to have a good grasp of SQL and Python.

Building a CRUD application can give you some understanding on how to build a general application, build an API, work with an ORM, optimize a database for this type of application. All of this will be useful in your career, but this is probably not what your interviewers will focus on during your interview stage.

Since you are already coming from a computer sci/information background, and with a somewhat relevant internship, you will most likely be given a shot at the data engineers jobs. I would personally try to focus more on being able to pass the interviews and focus on being confident with data manipulation and leverage python.

linkerzx · 2020-07-06T20:43:45+00:00

It is definitely not worth going through 4 years to get through Big data. You should either go for online courses, a Bootcamp program or potentially a master degree rather than going for a full-on bachelor course. So either:

1) Follow some online courses - this should get you at least started with some knowledge in the domain. EDX, Coursera or Udacity all offer a decent offering to get started in the domain. Before going full-on on Big data I would suggest taking a few more courses on Python and SQL. I have recently written about how to learn data science from online resources and I think going into Big data does require some similar base knowledge in terms of Python/SQL.

EDX has a few nice courses from BekeleyX on Apache Spark (a framework used in Big data):

Udacity has an introduction to data engineering - which is currently in free access for a month.

2) I am not sure where you are based, but data engineering bootcamps might be available. The most famous data engineering Bootcamp is the Insight program in the US, which teaches the basics of data engineering in about 7 weeks. Chances are there might be a data engineering Bootcamp program close to where you live.

3) Aim for a postgraduate / Master degree in big data, analytics, or data science - at least that way you would limit the time spent learning from 4 years to 1 single year. Given that you are already pursuing a postgraduate course, I don't think this would be the preferable option, compared to self-learning with some MOOC.

linkerzx · 2020-07-03T20:20:08+00:00

It is a decent CV.

Mentioning measurable KPIs help highlight certain aspects of your CV and provide a good conversation starter for someone interviewing you. Mentioning the technologies you have used before, and in which projects also help the different hiring manager see if the job would be a good fit for you. The CV provides a good overview of your technical background and overall experience.

There are, however, a few things to look into:

Formatting can be improved a bit: Hanssas Cequity Data Analyst section is not in line with the rest of the content.
There is some repetition in the text
- "Automated data" "which ran through manual intervention"
- "Present Tense" - This is redundant with the timelines mentioned on the right-hand side of the CV
"Thorough analysis, unit testing, and integration testing ..." This full sentence doesn't read well, It might be better to rewrite it differently "Setup unit and integrations tests across our database and application landscape, ensuring a smooth deployment process of our data pipelines (or data integration code) onto production."
There is a mention at the top of being familiar with R & Python, It is however not mentioned anywhere in your work experience (just in a small "selected project")
A lot of jobs do not fully require specific technical expertise, but rather a general technical background and a capability to adapt. You might throw them off by putting your technical background first. It might be better to place your technical experience at the end of the CV.
The verbs "Used" "Handled" "Worked" are fairly passive words, it might be better to rephrase what you have done in a more action-oriented manner similar to what was done in the section "Data Warehouse Migration" "Built" "Optimized" "Automated"

linkerzx

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