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Data science predictive modelling -ai /ml

5.00 to 8.00 Years   Bangalore   04 Oct, 2021
Job LocationBangalore
EducationNot Mentioned
SalaryNot Disclosed
IndustryRecruitment Services
Functional AreaSales / BD
EmploymentTypeFull-time

Job Description

data science predictive modelling -ai /ml in bangaloreJob DescriptionSummary:This role is positioned at the intersection of business and technology skill-sets for an individual looking for techno-managerial role in a vibrant work environment.The person in this role will lead client communications, business development initiatives, and analytical solutioning. The person who will justify this role should be able to ramp-up fast on business and technology aspects, very articulate, innovative and should have a structured approach towards problem solving. Hands-on-work on coding, dash boarding, business presentations, analytical modelling should be regularly expected based on business requirements.On the personal front, the person should be highly self-motivated, hard-working, articulate, passionate towards new solution building and able to lead, motivate, drive and at the same time handle multiple teams across subgroups and work with multiple stakeholders across legal, finance, pricing, marketing, and sales teams.

  • The ideal candidate would be adept at understanding customers business challenges and define appropriate analytics approach to design solution
  • Should be able to convert mathematical/ statistics-based research/ academic literature into sustainable data science solutions
  • This is a hands-on role, will be required to manage day to day delivery activities and guide team in executing analytics projects by analysing large volume of data
  • Research and bring innovations to develop next generation solutions in core functional areas related to Promotion Effectiveness, Forecasting with detrending methods, Digital Marketing, Customer Relationship Management (CRM), Campaign Management & Data Insights etc.
  • Provide technical thought leadership, coaching and mentorship in the field of data science in working with engineering and other cross functional teams
  • Evolve the approach for the application of machine learning/deep learning to existing program and project disciplines
  • He / She would also be responsible for creating Business & technical presentations, reports etc. to present the analysis findings to the end clients and for business development
  • This role requires excellent communication skills.
QualificationsEducational Criteria:
  • Masters in Statistics/Mathematics/Economics/Econometrics from Tier 1 institutions Or
  • Bachelor of Engineering or MBA from Tier 1 institutions Preferred
Additional informationTechnical Experience: (not all technical exposures are expected from one individual)Must Have:
  • Clustering, Decision Tree, Random Forest, Support Vector Machine, Na ve Bayes, GBM, XGBoost, Multiple linear regression, Logistic regression, ARIMA/ARIMAX
  • Tools: Python, SQL, Spark
Good to Have:
  • Hands on experience in developing models (end to end)
  • Model automation, Bayesian Inference/simulators, Bayesian Filters, GLM (Generalised Linear Models), GMM (Gaussian Mix Models) etc
  • Recommended system (ALS, MF, Collaborative filtering and Content Filtering), Deep Learning methods
  • Optimization Method like BFGS, differential evolutionary, MOO (multi objective optimization) etc
  • Sound understanding of mathematics like probability theory, differential calculus, Laplace and Furrier transformations etc
  • Tools: TensorFlow, big data, Experience on AWS platforms, Knowledge of any visualization tools like Tableau, Quick sight, Qlik sense, Power BI etc. is a plus
Functional/Domain Experience: Good exposure to Retail, and/or e-commerce Relevant Experience: 5+ years of hands on experience in CPG/Retail industry skillsartificial intelligence, Predictive modelling, Machinelearning qualificationM.E/M.Tech, B.E/B.Tech, B.Sc, MCA, BCA, BBA, MS/M.Sc(Science),

Keyskills :
support vector machinecustomer relationship managementbig datapower biqlik sensedata sciencedeep learningdigital marketinglinear regressionthought leadershipcampaign management

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