The role of data scientist is very very broad, encompassing data, domain, technology and most critical part the results, thus there are variety of positions under the role of DS. For better understanding purpose we shall segregate them into 2 types Business and Product.
To start lets see what do are the core skills that every data scientist needs ,then we will individually talk about types (Business, Product, Technology) and eventually how all three of them come together to successfully solve a business problem.
I have written this article, considering in mind that a lot of us are busy with our existing jobs, family commitments and so much more, my goal here is to make you understand that if you are looking for DS role, then how should you approach it from a Top Down Approach and get the maximum ROI for your time and money investment
So here is a list of things all DS should develop
1. DataAnalysis/ExploratoryAnalysis - You need to understand how to analyse data and extract key insights , That includes data visualisation and calculating key summary statistics. Proper exploratory analysis guides you throughout the rest of your project.
2. Data Pre processing - Transforming raw data into more useful data format which would include extraction,cleaning,transforming, aggregating, and de-aggregating data.
3. Applied Machine Learning - It doesn’t matter if you’ll directly be doing the modeling or not... machine learning is one of THE central technologies within this field. Applied ML includes data exploration & cleaning, feature engineering, algorithm selection, and model training.
Business Data Scientist
Mostly Business data scientists work on problems like
Marketing - Using sales data, customer profile data and marketing trend data to predict customer purchasing propensity.
Operations - Building predictive models and operation strategies for predictive maintenance and least operational disruption
Strategy - Building predictive forecasting models to help management take strategic decisions.
So at the core business data scientist working to improve business top line or bottom line through data analysis, predictive modelling, prescriptive analysis and testing. The emphasis is on the insight you can derive from the data
If you aspire to be a business data scientist, you need to focus on building your domain knowledge and more critically your communication skills, how do you communicate the results of your model and analysis will only determine your effectiveness.
Now you may be a little exhausted, to see the skills a DS need to develop and can it be developed by doing a certification or a course its your call, but if you were to my advice, follow the top down approach of learning and working side by side.
Product Data Scientist
Product data scientists work on building a software or a AI/ML model to solve a product specific problem. For product data scientists, the emphasis is on the product that you build. They work on problems like
1. E-commerce : Building an auto cataloging model to automatically tag products on the site, to improve search and product recommendations
2. Manufacturing : Developing Computer Vision based compliance management system for shop floor monitoring.
3. Consumer Products : Monitoring the health of senior citizens using smart watch
4. Customer Service : Building a NLP powered chatbot to help customer 24*7
As a product data scientist you will be actively working with the software engineers and product managers to build, deploy and test, so you will, so you’ll need to be able to speak a shared language. Be familiar with concepts like agile development, version control, and software architectures at a high level.
As a product data scientist managing databases and data pipelines could be a big part of your job. Become familiar with DB languages such as SQL. Also get to know other data formats (e.g. JSON files, web scraping, or unstructured data).
Now answering the most important question, how do I land up in a Data Scientist Job
Hopefully you now have better idea, what are the skills you need to develop to become a real data scientist and believe there are very few people on this planet, who posses all of these skills and those who have, have lear it gradually over the year through experience.
The First step, is to identify, where you want to be, does building new product excite you or does build forecasting models for business excite you.
Then Second step, is to ask yourself , where are you,
Are you working professional over the age of 30, having excellent domain knowledge, then you should develop the ability to understand solve a problem using the top down approach, thus for you, you should not jump to coding, but look at how to use available API's to solve the problem.
Focus on your domain, because that is your strength, so play on your strength.
The Third step, is not too rush, the field of DS is very very vast, if you start in the wrong direction, you may either end up hating it or hurting yourself of wasting time. remember its a journey.
If you have more questions on AI, you may want to look the following blog posts
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