The Data Science and Analytics COE is responsible for leading the creation and development of the overall strategy and direction of data science and advanced analytics at CDW – including ensuring continuity and seamless extension of existing programs, the development of a short- and long-term vision and roadmap, and defining and institutionalizing the role that data and analytics play throughout the organization as the fuel that drives and shapes CDW’s priorities and serves as an accelerant for CDW’s progress.
The Principal Data Scientist, reporting to the Manager of Data Science, will play a key role in Data Science and AI to foster value creation from the use of the organization's data assets, as well as the external data ecosystem. This co-worker will ensure that machine learning algorithms and data analytics are implemented appropriately, and the results are compiled into meaningful augmented analytical data products or dashboards and is shared with relevant stakeholders. This coworker creates value through data discovery, envisioning data-enabled strategies and enabling all forms of business insights and outcomes through analytics. The expectation is to identify and report on trends and patterns found within data and make recommendations for business and process improvement.
Key Areas of Responsibility
- Business Strategy: Work closely with business stakeholders as well as vendors to design, customize, implement, evaluate, improve, maintain and monitor the enterprise search engine
- Business Strategy: Translate business questions and concerns into specific hypothesis and quantitative questions that can be answered using data science and machine learning methodologies.
- Business Strategy: Approach the problems with a business-oriented mindset to develop an understanding and documentation of business problems, product requirements and success metrics.
- Data/Data Analytics: Transform, standardize and integrate data sets to develop data marts for data science use cases.
- Data/Data Analytics: Work as a data strategist and predictive modeler by researching, identifying and integrating datasets and innovative algorithms that drives products and services forward.
- Data/Data Analytics: Perform data exploration and foundational data analysis in support of long-term analytics objectives.
- Experimentation: Provide hypothesis and requirements to develop analytic capabilities, platforms and pipelines.
- Machine Learning: Develop new predictive models and enhance existing models to advance machine learning skills.
- Machine Learning: Implement highly optimized data analytics processing algorithms on big data batch and stream processing frameworks (i.e., Hadoop MapReduce, Spark, etc.).
- Machine Learning: Apply machine learning techniques (both supervised and unsupervised), data mining techniques, performing statistical analysis and building high quality prediction systems.
- Communication & Strategic Management: Partner with IT and Commercial teams to execute the data science roadmap.
- Communication & Strategic Management: Present insights and recommendations to audiences at the desired levels of understanding.
- Partner with business leaders to understand key objectives to design optimized data products.
- Research new and emerging data platforms and trends.
- Drive data innovation and transformation efforts across the enterprise.
- Leverage general business experience with knowledge to convert high level business objectives into functional and technical requirements, user stories and specifications.
- Map attributes to source including identification and documentation of transformation algorithms, scoring mechanisms, as necessary.
- Document business, data and technical specifications ensuring documentation is kept up to date and relevant.
Education and/or Experience Qualifications
- PhD or Master’s degree in Computer Science, Information Systems or equivalent IT knowledge/experience.
- 7+ years (or 5+ years with PhD degree) of relevant work experience doing Data Analysis, Data Engineering & Data Integration.
- Demonstrated ability as a Data Scientist, preferably from a role passionate about search and discovery.
- Excellent understanding of machine learning algorithms, processes, tools and platforms and ML concepts like multi-label classification, personalization, recommender systems, etc.
- Applied machine learning experience on large datasets/sparse data with structured and unstructured data.
- Experience in predictive modeling.
- 5+ years of frequent scripting languages use (Python, R, Jupyter Notebooks, Scala).
- Experience using classical machine learning and statistical algorithms using Python scikit-learn and/or other libraries: linear regression, logistic regression, LASSO, random forest, xgboost, k-means, neural networks etc.
- Practical experience with deep learning/deep neural networks, i.e., CNN, RNN, LSTM through Python libraries of Tensorflow/Keras, PyTorch and their optimizations for efficient implementation.
- Experience working with Big Data technologies, AWS, Hadoop, Spark, Impala, Kafka, NoSQL stores and RDBMS Oracle is a plus.
- Ability to execute analytical experiments methodically while outputting reproducible research.
- Highly detail oriented with the ability to handle multiple projects simultaneously.
- Great communication skills and presentation skills.
- Experience working with cloud-based data warehouses such as Redshift, Snowflake, BigQuery.
- Experience with cloud-based personalization and machine-learning applications.
- Experience working for consumer or business-facing digital brands.
CDW is committed to maintaining a workplace that is free of known hazards and to ensuring the safety, health, and well-being of coworkers and candidates for employment and their families, as well as the community.
CDW requires all coworkers be fully vaccinated against COVID-19, with the only exceptions being a documented, legally required medical or religious accommodation. Prior to starting with CDW, successful candidates will be required to: (i) be fully vaccinated against COVID-19 and provide CDW with proof of full vaccination; or (ii) apply for and receive a medical or religious-based accommodation to be exempt from the mandatory vaccination policy.