This is a relatively (surprising!!) new job position propping-up across California(& US) esp. from a utility companies like SCE. I do not know why they titled it as Data science analyst instead of Demand Forecaster position as both of the job requirements are same. Initially they set up the phone screen with Portfolio Planning and Analysis department panel (includes analysts, as well as a meteorologist). The phone interview went for 30 minutes with the panel asking my current work experience as a data analyst/scientist with emphasis on predictive models/big data techniques like hadoop in production though not very technical. Questions like what are the factors(features) that affect the electric consumption? They are expecting me to know the time series models like seasonality, trend, MA, ARIMA, ARIMAX etc. and how weather features affects the consumption like the usage of Air conditioners during Summer, working hours in a day, the day/night pattern that affect etc.They are looking for someone who can use the machine learning models from other industry setting (out-of-box thinking) for forecasting the short-term demand of electricity demand, renewable generation, and demand response up 90 days ahead. Also they welcome someone who can productionlize the R/SAS model using big data. The interviewers are patient enough to explain their expectation from the candidate. After the phone interview they called me for onsite interview within 15 days. The recruiter is very kind in setting up the interview with convenient dates. The interview include 1) case study (2) dimensional interview (3) technical presentation. (total of 3 hours) 1) Case study interview (1hr): The case study is related to the portfolio planning like in the B-schools from financial management coursework except the interviewer reads the scenario in words rather than we generally read from paper and slowly builds-up the case to make it narrow. The interviewer showed some graphs and expected me to calculate the dollar amount (under the area of curve) for different scenarios. Slowly the interview builds-up the scenario and create hypothetical situations to see how a decision affects if the company goes with X scenario to get break-even in dollars, time period, optimizing in terms of total cost etc. The interviewer is awesome! very professional and patient enough to listen the answers. 2) Dimensional Interview(1hr): A panel of 5 members took the interview. Most of them have pre-set of questions from a booklet. Every one reads the questions from the booklet and all of them keep on writing/recording what I had answered. The questions like see below: 3) Technical presentation (30 min): Technical presentation – You will need to prepare and give a 20 – 30 minute presentation on any topic related to statistical forecasting, data mining, or machine learning modeling. I presented my graduate school course project on statistics topic as my current work has propriety data. I didn't prepare well for presentation and chosen topic on causality which is neither interesting to me or for the panel/a non-relevant topic for forecasting team. Panel asked questions on my presentation topic I failed big time to address those. One of the panel member said directly that I should have presented some interesting topic on prediction like NLP based topic from my current work experience. Here I felt embarrassed as I didn't pick the topic which I rigorously studied in my current work experience/from school. I set up myself for failure in presenting the non-rigorous topic and couldn't address the questions from the presentation topic. I felt little impatient/frustrated in getting the "not-selected" news as they took over a month. However they promised me to tell the result with-in a week time. My guess is they interviewed 2 other candidates for the same position. They offered the job to 1st best candidate and I was kept in the waiting list till he/she accepted the offer/undergone the background check. Overall, the interview experience is good as process is rigorous and at the same time well within the reasonable time frame of 3 hrs. unlike some companies who take grilling/horrific 8 hrs in onsite interview.