Data Scientist - BFSI/FMCG/KPO

We have opening for Data Scientist for our client.

Please find below the Job Description

Requirements

Stakeholder Engagement Skills

- Working collaboratively across multiple sets of stakeholders - business SMEs, IT, Data teams, Analytics resources, etc. to deliver on project deliverables and tasks

- Identify actionable insights that directly address challenges / opportunities

- Articulate business insights and recommendations (based on model output) to respective stakeholders

- Understanding business KPI's, frameworks and drivers for performance

- Proficiency Level: Skill

Industry / Functional Expertise

- Customer / Marketing - pricing analytics, churn prediction, cross-sell / up-sell, Market Basket Analysis, Product Recommendation, Marketing Mix Modeling, Campaign design and effectiveness testing, Network Modeling, Customer segmentation, propensity analysis, customer lifetime value, profitability analysis, Customer experience (incl. voice of customer), CRM, Loyalty program management,

- Supply Chain / Spend: Demand & Supply Forecasting, Spend Analytics, Vendor Scoring, Pricing analysis (buy-side), product substitution analysis, product portfolio optimization, Tail spend analysis, logistics / network / route optimization, Contract Compliance

- Proficiency Level: Skill

Modeling and Technology Skills

- Deep expertise in machine learning techniques (supervised and unsupervised) statistics / mathematics / operations research including (but not limited to):

- 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

- Strong experience in specialized analytics tools and technologies (including, but not limited to)

- SAS, Python, R, SPSS (preferably two out of 4)

- Spotfire, Tableau, Qlickview

- For Operations Research (AIMS, Cplex, Matlab)

- Awareness of Data Bricks, Apache Spark, Hadoop

- Awareness of Agile / Scrum ways of working

- Identify the right modeling approach(es) for given scenario and articulate why the approach fits

- Assess data availability and modeling feasibility

- Review interpretation of models results

- Evaluate model fit and based on business / function scenario