Tags: CompositeJD
These are a composite set of skills extracted from various data analyst job descriptions. The idea is to generate a generic list of basic skills that I have and also ones that I can target. This is a work in progress.
### Skills/ Experience I have aligned to JD’s
- MS Excel basics and advanced skills, including knowledge of using VBA
- Education: Engineering degree, i.e quantitative or technical background
- Engaging with customers and clients, and providing analytical support to solve problems and extracting business requirements + formulating strategies.
- Coordinating with technical support services as a customer for various softwares and services.
- Experience in dealing with multiple stake holders.
- Experience in dealing with cross-functional and multi-national teams.
- Experience dealing with multiple products.
- [ ] Basic knowledge of building dashboards (Shiny, Tableau, Excel) : examples need to be demonstrated.
- Experience with Manual Data collection
- Experience with ERP systems (CRM, Sales, Purchase, Manufacturing modules).
- [X] Basic Extract Load Transform (ETL) knowledge, especially via ERP.
- SQL : including connecting with remote db’s (MySQL?, Postgres, Mongo)
### Other skills
- Knowledge of the Agile/Waterfall process
- Comfortable with Linux and CLI knowledge. Ability to handle a VPS.
- [ ] Docker : sample project displaying skills.
- Docker is not asked very commonly in data scientist profiles. However, it is certainly a strong skill to have as a data scientist.
- Numerical Analysis (Simulation driven design approaches like CFD/CAE)
- General scripting in python/bash/R/perl etc.
### Skills at various stages of completion The details will be fleshed out soon.
- TODO Better grip on fundamental statistics
- TODO Improve familiarity with Excel
- TODO Tableau : data viz/BI software (Examples of expertise to be formulated)
- TODO Intermediate SQL (Fluency + projects) [0/2]
- TODO Fluency in Data Cleaning with Python [/]
- TODO Fluency in ML with Python [0/1]
- TODO Unit testing approach in code
- TODO End to End project example with R (Data cleaning to ML)
- TODO End to end project in Python (Data cleaning to ML)
- TODO Gain knowledge in dealing with larger datasets.
- TODO Better expertise in ‘Data Wrangling’ and Exploratory Data Analysis (EDA)
- TODO Gain fundamental expertise in Cloud Platforms
- TODO Improving knowledge of how ML algorithms work
- TODO Big data
- TODO AWS fundamentals
- TODO Demonstrate an automation pipeline process