How do professionals with backgrounds in supply chain management switch their career into data science roles?

Question

What steps do professionals with supply chain management backgrounds take to transition into data science roles?

Answer 1

Professionals with supply chain backgrounds often transition to data science by acquiring relevant skills, such as programming, statistics, and data analysis, through online courses. Networking with professionals in the data science field and seeking mentorship can also be crucial. Tailoring their resumes to emphasize transferable skills and highlighting any analytical experience from their supply chain roles helps in securing data science job opportunities. Overall, a proactive and dedicated approach to learning and networking is key to a successful transition.

If you are interested in getting into this field, then check out this video about Deepak and how he successfully transitioned his career from Supply Chain to Data Science with a good salary hike just after completing Intellipaat's Advanced Certification in Data Science and AI.

Answer 2

Data science is a broad field which any professional with domain experience can transition into. Supply chain management professionals can consider this, break their experience into smaller segments and expand their expertise. This is how they can do it:

1. Domain Knowledge to be leveraged:

Data science encompasses multiple applications such as predictive analytics, optimization, and forecasting. Data scientists are used for these applications across sectors. A supply chain manager having expertise in logistics, demand forecasting and various segments can help expand he/she into this field.

2. Emerge as a master in core data science skills:

Programming: R and Python are the two languages that need to be obtained for any data work. Start off by using libraries such as Pandas for data handling and Scikit-learn for data learning.

Statistics & Machine Learning: Algorithms based on regression models and predictive analytics are what need to be studied as part of the statistics.

Data Visualization: Can use tools like Tableau or Matplotlib to help make visualizations that matter.

3. Finish Courses and Provide Certification:

Websites that provide courses such as Coursera or Udacity can help by providing a learning base for supply chain analytics. 

Business analytics alongside supply chain analytics certifications can assist in grasping a greater amount of domain specific and technical information.

4. Construct a Portfolio:

Constructing a multi demand forecasting model or logistics optimization algorithms while applying your supply chain experience can make for a great portfolio to showcase your SCM skills.