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Assistant Manager Data Scientist

4.00 to 7.00 Years   Bangalore   14 May, 2020
Job LocationBangalore
EducationNot Mentioned
SalaryNot Disclosed
IndustryManufacturing
Functional AreaIT Operations / EDP / MIS
EmploymentTypeFull-time

Job Description

  • Works with the business analyst to fully understand the business problem and how to deliver relevant insights that lead to actions.
  • Gathers, analyses, and model s data to solve complex business problems and evaluate scenarios to make predictions on potential future outcomes.
  • Fast paced agile experimentation across a range of business areas (Sales, Marketing, P&L etc).
  • Build analytic models and iterate to help demonstrate the business case to scale the solution.
  • Incorporate design thinking elements in building and developing solutions
  • Act as the go to expert on building diagnostic and predictive models through classical modelling and Machine Learning.
  • Able to scale and industrialize the solution on cloud-based platforms
JOB SUMMARY
  • Build data-science and algorithmic solutions to address business problems requiring diagnostic, predictive, and / or prescriptive analytics
  • Drive new value from insights from connecting external (Retailer, Econometric, Panel etc) and internal data sources
  • Innovate new data and analytic methodologies driven by local needs which feed into I&A s global product pipeline
  • The position will be primarily an individual contributor role working closely with the business interpreter and CCBT, CD, Supply Chain and other market teams.
  • Guide team on continuous improvement which will includes
  • improved ways of working
  • simplification and standardization
KEY REQUIREMENTS
  • B.E. / MTech or M.S. in a relevant technical field (Operations Research, Computer Science, Statistics, Business Analytics, Econometrics, or Mathematics). Experience of 4-7 years preferred.
  • Strong track record in solving analytical problems using quantitative and statistical approaches
  • Expert knowledge in Regression, Clustering, Random Forrest, Decision Trees, Optimization, Time Series, Probability, and other related advanced methodologies. Experience in applying Neural Networks would be a plus
  • Experience in designing and industrializing Analytical solutions
  • Expert knowledge of an analytics tool such as R, Python & Spark
  • Experience in communicating with clients and requirement gathering
  • Ability to manipulate and analyse complex, high-volume, high-dimensionality data from varying sources (Nielsen, SAP, Retailer ePOS; both structured and non-structured data)
  • Expert in working with cloud-based platforms like Azure, AWS and big data knowledge
  • Excellent communication, active listening and presentation skills and ability to communicate effectively with all levels in the organisation
  • Passion for delivering service excellence; and developing a culture of easy to do business with , where customer s needs are anticipated
  • Highly analytical mind-set with strong ability to identify, troubleshoot, problem solve and resolve issues. Passion for simplification and continuous improvement
  • Strong interpersonal skills with the ability to collaborate with team members to understand and develop technology solutions for business needs
  • Organised, strong time management skills and ability to prioritise multiple tasks in order to meet established deadlines
  • Team-player who is a proactive self-starter, with the ability to work independently
  • Strong ethical standards regarding the handling of confidential personal information
  • Ability to work quickly and accurately, especially under pressure; and within a cross-culture and global environment
  • Ability to work with a broad, virtual team
  • Proficiency in MS Office Suite and SQL desirable.
  • Analytically minded with good numerical ability and logical reasoning
  • Proficient in using R, Python or any other data mining tools.
  • Knowledge and experience in Hadoop (map reduce paradigm) etc.
,

Keyskills :
salesmis accountstat bankingms office suite big datams office data miningtime series

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