Data Scientist - Conglomerate

About Company:

A Fortune 10 Global Conglomerate

Position Definition

- Finance & Data Operations Data Science Team is tasked with delivering tangible value to business units within through data-driven decision making.

- This position is part of Finance & Data Operations Data Science team delivering advanced analytics projects for different businesses within . The individual will join a growing global data science organization spanning both on/offshore.

- Incumbent is responsible for developing analytical models for projects collaborating with different business stakeholders & other partners and working across a range of technologies and tools.

- The ideal candidate has strong background in quantitative skills (like statistics, mathematics, advanced computing, machine learning) and has applied those skills in solving real world problems across different businesses / functions

Modeling and Technology Skills (and/or)

- Advanced Machine learning techniques: Decision Trees, Neural Networks, Deep Learning, Support Vector Machines, Clustering, Bayesian Networks, Reinforcement Learning, Feature Reduction/engineering, Anomaly deduction, Natural Language Processing (incl. Theme deduction, sentiment analysis, Topic Modeling), Natural Language Generation

- Statistics / Mathematics: Data Quality Analysis, Data identification, Hypothesis testing, Univariate / Multivariate Analysis, Cluster Analysis, Classification/PCA, Factor Analysis, Linear Modeling, Logit/Probit Model, Affinity & Association, Time Series, DoE, distribution/probability theory

- Operations Research: Sensitivity Analysis - Shadow price, Allowable decrease or increase, Transportation problem & variants, Allocation Problem & variants, Selection problem, Multi-criteria decision-making, models, DEA, Employee Scheduling, Knapsack problem, Supply Chain Problem & variants, Location Selection, Network designing - VRP, TSP, Heuristics Modeling

- Risk: Simulation design and high-performance computing, GARCH modeling, Macro-economic / Market behaviour modeling

- Process Analytics: Process Discovery / Mining, BottleNeck analysis, Confirmation Testing, Process Benchmarking, Gap-to-Potential Assessment, SAP Data Models, SAP Table Structures (across SAP Modules - 5-6 of the following: General Ledger Accounting, Accounts Payable, Accounts Receivable, Purchasing, Inventory Management, Material Planning, Invoice Verification, Material Requirement Planning (MRP), Warehouse Management, Vendor Valuation, Sales, Sales, Shipping and transportation, Billing or Invoice generation, Bills of Material (BOM), Sales Information system, Credit Control, Sales and production Planning, Demand Management, Material Requirement Planning, Capacity Requirement Planning

Experience

- 5 years of relevant experience

- Advanced university degree in Mathematics, Statistics, Engineering, Economics, Quantitative Finance, OR, etc.

- Good interpersonal communication skills and influencing skills

- Eagerness to learn and ability to work with limited supervision