Data Scientist

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Here at Lenovo, we believe in smarter technology for all, so we spend our time building a society that’s brighter and more inclusive. And we go big. No, not big—huge.

We’re a US$60 billion revenue Fortune Global 500 company serving customers in 180 markets around the world. Focused on a bold vision to deliver smarter technology for all, we are developing world-changing technologies that power (through devices and infrastructure) and empower (through solutions, services and software) millions of customers every day and together create a more inclusive, trustworthy and sustainable digital society for everyone, everywhere.

The one thing that’s missing? Well… you...

Description and Requirements

This position is responsible for identifying and designing customized predictive / advanced statistical models enabling product merchandise optimization, effective pricing & promotion strategy development and supporting online operations efficiently for Lenovo's cutting edge eCommerce Analytics Department. 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 and visualization
• Masters Degree in any quantitative disciplines such as Engineering / Statistics / Applied Mathematics / Economics / Computer Science from a top tier University required
• Good knowledge of eCommerce, product & pricing analytics, Digital Analytics and PC industries
• Develop tools that support eCommerce and analytics division focusing on product planning & forecasting, product recommendations, optimum pricing, inventory optimization and customer preference modeling
• Ability to quickly analyze problems and bottlenecks to come to logical and optimal solutions
• 4 to 6 years of data science, analytics experience designing tools for quantitative modeling and analysis, including optimization and simulation
• Hands on experience in building & implementing predictive models using machine learning algorithms
• Use your judgement to craft analytics solutions to complex business problems, prototype and demonstrate value generation from data science initiatives
• 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 R, Python, SQL, MS Excel, SPSS, 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 preference over time for product portfolio optimization
• Optimization: Price sensitivity and promotion optimization models, operation research techniques
• Proficiency in machine learning techniques and ensemble modeling
• Knowledge of forecasting techniques using ARIMA, ANOVA, Regression, Winterholt, Time Series, Logistic, Exponential
• Good to have knowledge of Deep Learning and Neural Network techniques
• Product mix modeling using MDS (Multidimensional Scaling), Factor Analysis and Clustering
• Cross-sell & Up-sell modeling: Product affinity model, propensity to respond, predicted sales value, predicted next purchase

Models to optimize effectiveness of customer contacts and strategies as well as and service channel preference