Lenovo : Data Scientist

Brief Description of position:

This position is responsible for identifying and designing customized predictive / advanced statistical modeling in eCommerce, marketing, finance and online operation areas for Lenovo's cutting edge eCommerce Analytics Department using Big Data platforms. To succeed in this position, working in a SCRUM environment, helping with analysis, development and deployment of multiple projects is a must.


Essential Responsibilities:

  • Research, conceptualize, develop and drive initiatives around Big Data, machine learning, data analytics, visualization, modeling, anomaly detection, clustering, segmentation and regression
  • Masters Degree in any quantitative disciplines such as Statistics/ Applied Mathematics/ Business Management, Economics, Computer Science or Finance from a top tier University required
  • Good knowledge on eCommerce, Digital Analytics and PC industries
  • Develop tools that support eCommerce and analytics division focusing marketing campaigns attribution, understanding the impact of brand perceptions, customer profiling, market penetration, competitor pricing and market segmentation
  • Ability to quickly analyze problems and bottlenecks to come to logical and optimal solutions
  • 4 to 6 years of analytics or data science experience designing tools for quantitative modeling and analysis, including optimization and simulation
  • Help develop a Data Science/ML/Analytics acumen within the larger eCommerce business teams, training them towards full adoption by connecting the dots between statistical and business concepts
  • Narrate compelling stories and present the insights / findings developed

Position Requirements:

  • Excellent verbal and written communication & presentation skills - Must be highly versed in analytic methodologies
  • Should be comfortable in undertaking and delivering projects covering Exploratory Data Analysis (40%), Analytics Automation (30%), Statistical Analyses & Modelling (30%)
  • Strong experience in advanced statistical / data mining tools like SPSS, R, Python, SQL, MS Excel, MS PowerPoint, etc.
  • Experience in Digital / Web Analytics and platforms like Adobe Analytics / SiteCatalyst or similar technologies
  • Knowledge of business intelligence report design and development within Tableau, PowerBI, QlikSense or other similar technologies
  • Must have a track record of aligning activities with business strategies and measuring impact on business results
  • Real-Time Analytics: real-time scoring and offer generation models, assessing customer behavior over time for marketing event triggers to support automated marketing programs
  • Optimization Analytics: Price sensitivity and promotion optimization models
  • Proficiency in machine learning and big data platforms like Hadoop, Apache Spark, etc
  • Knowledge of forecasting techniques using ARIMA, ANOVA, Regression, Winterholt, Time Series, Logistic, Exponential and Neural Network techniques
  • Product mix modeling using MDS (Multidimensional Scaling), Factor Analysis and Clustering
  • Customer Profiling, Scoring, Customer Equity and Lifetime Value Modeling
  • Acquisition models: Prospect targeting, prospect potential value, product positioning, key influencers, product awareness
  • Retention & Attrition models: loyalty, store choice, customer service, satisfaction, propensity to churn, attrition models
  • Cross-selling models: Product affinity model, propensity to respond, predicted transaction rates, predicted sales value, predicted next purchase
  • Models to optimize effectiveness of customer contacts and strategies as well as and service channel preference
Minimum Qualification:

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