Cascade Data Labs is a boutique consulting agency (operating as part of Kin + Carta) with end-to-end experience helping Fortune 500 companies form and execute their analytics strategy and infrastructure. We believe strongly that the difference between analytics success and failure comes down to practitioner-level understanding of the “details” presented across a variety of disciplines: data collection, organization, and engineering in a rapidly evolving technological landscape; analytical inference on multi-dimensional data sets; and the communication of findings to business stakeholders in visually compelling ways. As such, we seek a new breed of data professionals that can cut across these disciplines as project requirements dictate, blurring the lines between data analyst, scientist, and engineer, with the ability to work across a multitude of projects and contribute across various aspects of data product . While our culture promotes continual development and multidisciplinary growth, over time employees may gravitate towards a specific specialism
and thrive in building a deep expertise in their domain of interest.
Ideal candidates will have strong quantitative backgrounds and analytical discipline. While they will have some demonstrated ability to write code, they will not have learned programming languages for the sake of building their resume, but rather as a means to express their intellectual curiosity and analytical voice. Cascade Data Labs will provide a platform and training to help them reach their full potential. We are seeking candidates with all levels of experience; intern to senior-level.
- Analyze a collection of raw data sets to create meaningful impact to large enterprise clients while maintaining a high degree of scientific rigor and discipline.
- Engineer data pipelines and products to help stakeholders make and execute data driven decisions.
- Communicate analytical findings in an intuitive and visually compelling way.
Potential Responsibilities (depending on aptitude, project, and seniority):
- Creating highly visual and interactive dashboards via Tableau, PowerBI, or custom web applications
- Conducting deep dive analysis and designing KPIs to help guide business decisions and measure success
- Engineering data infrastructure, software libraries, and APIs supporting BI and ML data pipelines
- Architecting cloud data platform components enabling the above
- Building and tracking project timelines, dependences, and risks
- Gathering stakeholder requirements and conducting technical due diligence toward designing pragmatic data-driven business solutions
- Bachelors or Masters degree in quantitative studies including Engineering, Mathematics, Statistics, Computer Science or computation-intensive Sciences and Humanities. Recent graduates should include GPAs in their resumes from degrees obtained in the last 5 years.
- Proficiency (can execute data ingestion to insight) in programmatic languages such as SQL, Python, R
Candidates are not expected to possess all of the below skills but should possess a demonstrated aptitude and excitement to learn more of them. Proficiency across these qualifications will help dictate seniority.
- Proficiency in visualization/reporting tools such as Tableau and PowerBI or programmatic
- Proficiency scripting in UNIX environment
- Proficiency in big data environments and tools such as Spark, Hive, Impala, Pig, etc.
- Proficiency with cloud architecture components (AWS, Azure, Google)
- Proficiency with data pipeline software such as Airflow, Luigi, or Prefect
- Ability to turn raw data and ambiguous business questions into distilled findings and recommendations for action
- Experience with statistical and machine learning libraries along with the ability to apply them appropriately to business problems
- Experience leading and managing technical data/analytics/machine learning projects