Sanofi-Aventis Singapore Pte Ltd – Time Series Analyst – Forecast Methodology Designer

Company
Sanofi-Aventis Singapore Pte Ltd
sanofi.com
Designation
Time Series Analyst – Forecast Methodology Designer
Date Listed
18 Nov 2015
Job Type
Entry Level / Junior Executive
Intern/TS
Job Period
Flexible Start, For At Least 3 Months
Profession
General Management
Industry
Healthcare / Fitness / Sports
Location Name
38 Beach Road, South Beach Tower Singapore 189767
Allowance / Remuneration
$800 - 1,500 monthly
Company Profile

The ambition of Sanofi is to become a diversified global healthcare leader, focused on patients’ needs.


The largest pharmaceutical company in Europe and in emerging markets, Sanofi is the fourth largest worldwide. The Group’s vaccine division, sanofi pasteur, is the world leader for human vaccine production and commercialization.

With nearly 100,000 employees in over 100 countries, Sanofi has core strengths in the field of healthcare: a worldwide presence, market leadership in vaccines, major biological products and a strong and long-established presence in emerging markets.

Company business activities also include consumer healthcare products, generics and animal health products.

Job Description

Mission

·         To Analyse the Sales History Time Series of the Asia / Jpac region affiliates

·         To Propose new forecasting methodologies and algorithms suitable to our context

·         To Estimate the expected benefits VS the effort required to implement

Primary Activity

As per today, monthly forecast are calculated from monthly sales history, using Multiple Linear Regression algorithm. Getting Weekly (or even Daily forecast) would be desirable to sanofi as our plants are running Weekly Planning Runs, in order to do that, we need to start from Daily Times Series. The first activity of the candidate would be to analyse each market to determine the significant calendar effects :

·         Fixed Holidays

·         Variable Holidays possible across the region (Chine New Year, Muslim Holy festivals, Easter…)

·         Trading day effect

·         Number of working days per period

·         End of the month / End of the Quarter effects

·         The candidate should be able to propose suitable Tools / Methods to correct these effects in our Time Series (X12 ARIMA, TRAMO/SEAT or  any other method…).

·         The second activity would be to analyse and classifiy the diferent profiles of products and to propose suitable time buckets and methods of forecasting for each of them (could be daily, weekly or even monthly for slow moving products). The methods will be implemented in the current tool if the required algorithms are available, if not, using other tools (R for instance).

·         The third activity would be to measure the performance of the selected methods by forecasting 2015 out of the Sales histories of 2014 and previous years, and compare the results with those obtained with the current Methods and Tools. From this measure, the benefits of the new methods will be calculated, and compared with the required efforts.

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