Junior Data Engineer

Company Description

Its an exciting time at VeroSource as we continue to grow and expand our footprint into the local digital health market and beyond. We are a progressive, fast-growing company led by a team of experienced Business and IT professionals that has gained a reputation for excellence. We enjoy challenging and rewarding work and the chance to collaborate with an amazing team. We offer a competitive salary and benefits package and promote a healthy work-life balance. Come join us and be part of the team!

**Where you come in
As a Junior Data Engineer, you will work within the Data Science team and with the Business Development and Solutions teams to develop and produce data pipelines and craft useful datasets for creating machine and deep learning models that enrich VeroSource and client applications with accurate data analysis, predictions, and recommendations.Job Responsibilities include, but are not limited to:**

• Understand business needs and develop solutions through machine learning or other advanced analytics

• Work with different members of the team to identify data requirements and help to develop and implement solutions

• Help implement automated data pipelines for transforming client data

• Data cleaning and feature engineering on datasets to improve model performance

• Decipher and solve business problems by developing predictive models

• Analyze data and generate visualizations and reports on those analyses

• Develop process improvements and integrate new systems with existing frameworks

• Validate program operation by conducting QA testing

• Identify and escalate data issues to support continuous process improvements

• Maintain historical records by documenting program development and revisions

Requirements

Required skills:

• 1-5 years of experience

• Strong analytical and problem-solving skills

• Proficient in the use of Python. Proficiency in R would also be a great asset.

**Nice to have (but not required):

• Knowledge of cloud service providers Machine Learning tools, such as Amazon AWS and Microsoft Azure

• Data visualizations skills using Tableau, Power BI or similar

• Experience working with Spark and Resilient Distributed Datasets

• Experience with data partitioning and partitioning strategies

• Experience with RDBMS and data modeling

• Fluency working with machine learning frameworks such as Scikit-Learn and TensorFlow

• Experience implementing machine learning models in production environments

• Experience with artificial intelligence

• REST API Development

• GIS knowledge and experience, particularly experience with Esri Online products