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Assistant Manager - I&A Finance

7.00 to 8.00 Years   Bangalore   15 Mar, 2021
Job LocationBangalore
EducationNot Mentioned
SalaryNot Disclosed
IndustryManufacturing
Functional AreaFinance / Accounts / Tax
EmploymentTypeFull-time

Job Description

JOB TITLE: Assistant Manager, Finance Data ScienceLOCATION: UniOps Bangalore MAIN PURPOSE OF JOB:

  • Finance as a function has been evolving quite rapidly in Unilever which is increasingly placing a lot of emphasis on Data and the Science to get maximum out of data. The function has sub-functions like Supply Chain Finance, Procurement Finance, CD Finance, Brand Finance, Tax, Treasury, Insurance, Global Performance Management and Corporate Audit. Most of these roles are carried out through Country Category Business Teams (CCBTs) or Finance Excellence Teams (FETs). Each of these has a huge amount of data at its disposal. This presents opportunities to perform Diagnostic, Prescriptive & Predictive Data Science.
  • Key Diagnostic analytics will include concepts like Anomaly Detection & Association Analysis,
  • In the Prescriptive & Predictive spaces, Pattern Recognition and Forecasting
  • Visualisation to reflect the results of Data Science work for consumption by end users
  • This is an exciting new role in the Information & Analytics Finance team, which is tasked to deliver maximum value from data & data science in the Finance Area.
KEY ACCOUNTABILITIES:
  • Apply data exploration and analysis techniques to examine data available from multiple disparate sources, with the goal of improving understanding of Profit & Loss, Working Capital, Cash Flow
  • Apply statistical and predictive modeling concepts, clustering and classification techniques, and recommendation algorithms to help obtain appropriate forecasts or identify anomalies that need to be corrected
  • Lay the groundwork for reinforcement learning systems for eventual operations optimization
  • Drive processes for extracting and using data in creative ways, and create new lines of thinking within the Finance function.
Specifically, this role will focus development of data-science and algorithmic solutions that power Unilever s Finance function. The role will integrate design inputs provided the global Data Science COE and in-market data scientists working in Finance; and prioritize the most critical features into their models ensuring a healthy balance between global scale and local relevance.KEY REQUIREMENTS
  • B.S. or M.S. in a relevant technical field (Operations Research, Computer Science, Statistics, Business Analytics, Econometrics, or Mathematics). Analytical Development experience of 7+ years preferred.
  • Experience in digital native company applying advanced analytics with clear vision for applying previous experience in consumer goods industry. Prior experience with Ecommerce space is a strong plus.
  • Experience with digital analytics (Next Product to buy, cross channel attribution modeling, digital analytic tools, dynamic ecommerce pricing, web scraping etc).
  • Strong track record in solving analytical problems using quantitative and statistical approaches
  • Expert knowledge in statistics (Regression, Clustering, Random Forrest, Decision Trees, Optimization, Time Series, Probability, and other related advanced methodologies)
  • Adapt in selecting features and optimizing classifiers.
  • Good knowledge of an analysis tool such as Alteryx, Angoss, KNIME, Microsoft PowerBI etc
  • Expert knowledge working with and coding in R/Sparkly R, Python/PySpark and Microsoft Azure Machine Learning
  • Experience in Machine Learning Toolkits (Tensor Flow, Caffee) is a plus
  • Passion for empirical research and for answering hard questions with data
  • Ability to apply Agile approach is desirable
  • Ability to communicate complex quantitative insights in a precise, and actionable manner
,

Keyskills :
salesmisaccountstime seriessupply chaindata scienceclear visionweb scrapingbrand financeconsumer goodsdecision treesmicrosoft azureworking capitalcomputer sciencemachine learningdigital analyticscommercial models

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