Data Analyst

Data Analyst: This role applies industry-leading methodologies for working with large datasets to extract meaningful business insight and creatively solve business problems. This role will apply advanced methods and algorithms for identifying trends, predicting outcomes, and alerting the business to potential issues. Additionally, the Data Analyst is expected to present insights and recommendations to non-technical audiences and explain the benefits and impacts of the recommended solutions.

This role will create analytical models and datasets while working with a Data Engineer to develop code for extracting data from source systems, which will include the Relational Enterprise Data Warehouse, Operational Data Store, and Could platforms. The ideal candidate will also be passionate about developing machine learning models using Azure Databricks and/or Azure ML Studio, or a comparable platform for operationalizing Machine Learning workloads. Multiple could platforms expertise is desired.

Responsibilities:

• Engage with business partners and stakeholders to understand business problems and translate them into data analytics solutions.

• Coordinate and collaborate with data engineering, analytic engineering, and other resources to achieve business goals.

• contribute to the end-to-end development and deployment of predictive and prescriptive models.

• Explore large datasets using modeling, analysis, and visualization techniques.

• Communicate results, analyses, and methodologies to technical and non-technical senior level stakeholders.

• Ability to mentor, coach, and lead others.

• Contribute to and help build ML/AI vision to support business strategy.

Required Knowledge, Skills, Abilities (Qualifications):

• Degree in Data Science, Machine Learning, Applied Mathematics/Statistics, or a related field.

• 3 years of experience applying data science, AI/machine learning, or analytics techniques to business problems.

• Experience with supervised and unsupervised machine modeling techniques, with a focus on time-series forecasting.

• Experience solving real-world problems using programming languages such as SQL, Spark, and Python, and deploying solutions to enterprise systems in data engineering and data analytics.

Ability to work on data Engineering and bigdata programming tools and technologies such as pig, Hive, Hadoop