General Position Definition
- Incumbent is responsible for supporting the development of analytical models for projects collaborating with different business stakeholders & other partners and working across a range of technologies and tools.
- The ideal candidate has good background in quantitative skills (like statistics, mathematics, advanced computing) and has applied those skills in solving real world problems
- Support the Data Analytics team in design and execution of analytics projects
- Work with data and technology experts to help execute analytics projects and deploy solutions
- Deep expertise in machine learning techniques (supervised and unsupervised) statistics / mathematics / operations research including (but not limited to):
- Advanced Machine learning techniques (Mandatory): 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 (Mandatory) 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 (Good to have; Added Advantage): 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 (Good to have; Added Advantage): Simulation design and high-performance computing, GARCH modeling, Macro-economic / Market behaviour modeling
- Strong experience in specialized analytics tools and technologies (including, but not limited to)
- SAS, Python, R, Alteryx, SQL (preferably two out of 5)
- Spotfire, Tableau, Qlickview, Power BI (preferably 1 out of 4)
- Identify the right modeling approach(es) for given scenario
- Assess data availability and modeling feasibility
- Review interpretation of models results
- 1+ Year/ Fresher with Advanced university degree in Mathematics, Statistics, Engineering, Economics, Quantitative Finance, OR, etc.
- Good communication skills
- Eagerness to learn and ability to work under tight deadlines
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