Senior Data Analytics Engineer
How is this team contributing to the vision of Providence?
Providence is committed to improving the caregiver and patient experience through simplification, modernization, and innovation. The Shared Services Analytics (SSA) Data Engineering and Analytics team is key to this mission, focusing on modernizing our analytical capabilities and prepares vital data frameworks for financial last mile reporting. By leveraging data-driven insights, this team plays a pivotal role in supporting Providence's strategic objectives.
Our Team culture:
- Work environment, which is collaborative and driven by Learning, exploration & experimentation mindset.
- Empowering & Enabling individuals and teams to realize their full potential.
- Focus on outcomes, solving users pain points & predictable delivery.
- Data driven decision making on vision & roadmap of Products.
What will you be responsible for?
We are in search of a candidate with a versatile skill set encompassing data analysis, engineering, machine learning, and programming. An ideal fit for this role would be someone who has experience in building data platforms and pipelines and has successfully transitioned to machine learning. The candidate should demonstrate expertise in tackling complex data science problems, extracting meaningful insights, and contributing to data-driven decision-making. Collaboration is pivotal to success in this position, and we expect the candidate to thrive in a team-oriented environment. Moreover, we greatly value a strong commitment to delivering high-quality results and a keen focus on engineering excellence.
- Collaboration and Stakeholder Engagement: Collaborate with stakeholders and cross-functional teams, including data engineering and product management, to understand requirements and ensure data solutions align with business objectives.
- Data Engineering Excellence: Design and develop robust data pipelines, ETL processes, and data integration strategies to ensure seamless data flow from various sources into the Snowflake /DataLake.
- Reporting, Advanced Analytics and Modeling: Design and Create Power BI Dashboard, Conduct sophisticated data analysis and use innovative models to solve complex business problems. Utilize state-of-the-art statistical and machine learning techniques to extract valuable insights.
- Continuous Learning and Innovation: Stay updated with the latest advancements in data science and identify opportunities to integrate cutting-edge technologies and methodologies. Lead research initiatives to explore new approaches to data analysis.
- Exploratory Data Analysis (EDA): Conduct EDA to gain deep insights into data patterns, structures, and characteristics. Use visualizations to communicate effectively.
- Statistical Analysis and Validation: Engage in statistical analysis and hypothesis testing to validate assumptions.
- Machine Learning Implementation (Good to have): Develop and deploy advanced machine learning models to address specific business challenges effectively. Evaluate and fine-tune algorithms for improved accuracy and performance.
- Presentation and Communication: Present findings and insights to stakeholders/ non-technical users through data visualizations and reports in a clear and understandable manner.
- Documentation and Knowledge Sharing: Document the data analysis process and methodologies for future reference and knowledge sharing.
- Cultural Enrichment: Foster a culture of innovation, knowledge-sharing, and continuous improvement within the data science team.
Who are we looking for?
- 3+ years of hands-on experience in building data analytics, data engineering and machine learning solutions (Good to have).
- Solid experience with Azure Stack services and Snowflake.
- Proven expertise in building Interactive Dashboards in Power BI.
- Good to have expertise in advanced statistical analysis, machine learning, and predictive modeling.
- Proficiency in programming languages is preferably Python.
- Good understanding of data governance, security, and privacy practices.
- Excellent communication and presentation skills, with the ability to convey technical concepts to non-technical audiences.
- Exposure in building analytical solutions utilizing real-time and semi-structured data is big plus.
- Bachelor's or master's degree in computer science, or a related field.