General Information

Req #
Career area:
Software Engineering
United States of America
North Carolina
Tuesday, August 3, 2021
Working time:

Why Work at Lenovo

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 not just a Fortune Global 500 company, we’re one of Fortune’s Most Admired. We’re in 180 markets, working with 63,000 brilliant colleagues and counting. And we’re known for the world’s most complete portfolio of smart technology, from devices to software to infrastructure.

With our ingenuity, we help millions—not just the select few—experience our version of a smarter future. 

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

Description and Requirements

We’re looking for a Data Scientist within the Advanced Innovation Center (AIC), Cloud and Software solutions group at Lenovo. In this role you will execute advanced analytics modeling and machine learning techniques based on exploratory data analysis from complex and high-dimensional datasets, to recognize patterns, identify opportunities, and generate valuable customer insights in support of innovative business decisions for our products.

You’ll be a part of highly dynamic agile software development team and will work on the data processing and modeling solutions from the conceptual stages through the development cycle and deployments. You’ll be responsible for developing and maintaining machine learning models that help to gain insights about Lenovo customers, understand the behavior of end-users and improve their consumer experiences. The ideal person for this role is highly analytical, thinks about problems in a structured way, is passionate about generating hypotheses for business problems, and is excellent at delivering actionable insights and recommendations.

Duties and Responsibilities

Blend data from diverse sources, process and prepare the dataset for exploratory data analysis
Navigate large complex datasets to produce descriptive analysis, correlations, and insights
Design, develop and optimize effective machine learning models for user profiling and recommendation applications
Working with engineering team to implement models efficiently as part of a high-performance, fault-tolerant, secure, and scalable data pipeline that can scale with business and data growth
Conduct ad-hoc data analysis and innovation around data visualization
Work closely with product managers to understand business goals and priorities, and the role data plays in achieving them, identify gaps in existing data collections and proactively work to fill them
Present analyses and recommendations to cross functional stakeholders for decision making in presentation, verbal and/or communication forms
Recommend ways to improve data reliability, efficiency, and quality

Basic Qualifications

MS or PhD in Data Science, Machine Learning, Computer Science, Computer Engineering, Electrical Engineering, Physics, Applied Mathematics, or in other quantitative disciplines.
7+ years of experience with Python programming and data science tools (Pandas, NumPy, scikit-learn, TensorFlow, Jupyter Notebook, etc.).
5+ years professional experience in Machine Learning pipeline - data ingestion, feature engineering, model selection, training, and prediction, diagnosing over fitting and model deployment.
5+ years working experience with Spark ML libraries.
5+ years of experience with SQL language.

Preferred Qualifications

Deep understanding of Recommender System algorithms.
Build predictive models and machine-learning algorithms, and combine models through ensemble modeling
Experience with various database, cache, and messaging systems such as Redis, MongoDB, ElasticSearch, Kafka, as well as standard RDBMS and graph database solutions.
Strong ability to understand and organize structured and unstructured data from various sources
Experience working with cloud-based data solutions (AWS preferred).
Professional experience with Python development
Present information using data visualization techniques
Propose solutions and strategies to business challenges
Collaborate with engineering and product development teams
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any federal, state, or local protected class.