What are the responsibilities and job description for the Direct Client - Mid Level Data Scientist / Data Analyst – Supporting Customer Analytics Projects position at The AES Group?
Direct Client - Mid Level Data Scientist / Data Analyst Supporting Customer Analytics Projects
Location : Seattle, WA (Onsite)
Job description
This job contributes to 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 on a cross-functional team of innovation leaders supporting strategic initiatives that help shape and define the future of Client.
Models and acts in accordance with Client's guiding principles.
Looking at data from a human lens, will not be doing hands on lab testing
Tops 3 Skills Needed
SQL and Python
3 Years
Customer Data Analytics
3 Years
Years of Experience :
Minimum of 3 years of experience within data analysis field or discipline
Technology requirements :
Microsoft Office tooling
Exposure and business-applicable experience in several data ETL ( SQL, Python , DataBricks, Java, Ruby, Pig, Teradata, Oracle)
SQL and Python are 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 to 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 process to level up Lab analytics)
Contributes to analytic project proposals
Promotes and advocates for value of analytics and data among peers
Provides knowledge share and mentorship to team in databases, tools, access, data prep techniques
Nice-to-Haves :
Retail, customer loyalty, and eCommerce experience, preferred
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