Benefits:

Competitive salary

Opportunity for advancement

Training & development

Direct Client - Direct Client - Mid-Level Data Scientist / Data Analyst – Supporting Customer Analytics Projects Location: Seattle, WA (Onsite)

Job description

This job contributes to the client's success by guiding business decisions through utilizing data analysis and consulting that results in predicting directional outcomes, understanding complex data relationships, and developing a quantitative return on investment. This position partners with a cross-functional team of innovation leaders supporting strategic initiatives that help shape and define the future of the Client.

Models and acts in accordance with the Client's guiding principles.

Looking at data from a human lens, will not be doing hands-on lab testing

Tops Skills Needed

1 | SQL and Python | 3+ Years 2 | Customer Data Analytics | 3+ Years

Years of Experience:

Minimum of 3+ years of experience within the data analysis field or discipline

Technology requirements:

Microsoft Office tooling

Exposure and business-applicable experience in several data ETLs (SQL, Python, DataBricks, Java, Ruby, Pig, Teradata, Oracle)

SQL and Python are a priority, data bricks preferred

Experience with Azure, AWS Databricks preferred

Required background - Skills

Ability to apply knowledge of multidisciplinary business principles and practices to achieve successful outcomes in cross-functional projects and activities

Exposure and business-applicable experience in several Modeling & Machine Learning Techniques (regression, tree models, survival analysis, cluster analysis, forecasting, anomaly detection, association rules, etc.)

Degree or certifications required:

Education: BA/BS with concentration in quantitative discipline - Statistics, Math, Comp Science, Engineering, Econ, Quantitative Social Science, or similar discipline

Daily Responsibilities:

Extracts data from various databases; performs exploratory data analysis, cleanses, massages, and aggregates data

Applies basic statistical concepts and descriptive statistics to understand and describe relationships in data

Builds predictive models and complex descriptive analytics, such as clustering and market basket analysis

Participates in discussions with business partners to define business questions and consult

Creates impactful visual representations of analytic insights and concise summaries of methodology geared to audience needs; presents selected portions to stakeholders

Provides analytic support (code documentation, data transformations, algorithms, etc.) to implement analytic insights and recommendations into business processes (e.g., automation of the process to level up Lab analytics)

Contributes to analytic project proposals

Promotes and advocates for the value of analytics and data among peers

Provides knowledge share and mentorship to team in databases, tools, access, and data prep techniques

Nice-to-Haves:

Retail, customer loyalty, and eCommerce experience preferred

Data bricks experience

Larger data sets experience

Supply chain or UX background

Innovation and supply chain experience preferred

Smart sheets