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.

Skill 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
• Experience in dealing with customers and clients, and providing analytical support to solve problems and extracting business requirements + formulating strategies.
• Experience in being a customer and dealing with technical support services for various softwares and services.
• Experience in dealing with various stake holders.
• Experience in dealing with multiple teams (intra and extra departmental).
• Experience dealing with multiple products.
• [ ] Basic knowledge of building dashboards (R Shiny) : 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. This has to be highlighted in the CV.

## Other skills

• Comfortable with Linux and CLI knowledge. Ability to handle a VPS.
• Dealt with different forms of data analysis over 6 years.
• [ ] 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.

## Skills to be developed The plans and details for this list of skills 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 Knowledge of the Agile/Waterfall process
• 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 Atleast 1 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