Key Responsibilities:
Data Analysis and Interpretation:
- Analyze large, complex datasets to extract meaningful insights and trends.
- Develop and implement statistical models and machine learning algorithms.

Data Engineering:
- Design, build, and maintain scalable data pipelines.
- Ensure data quality and integrity across various data sources.
- Optimize data storage and retrieval processes.

Collaboration:
- Work closely with cross-functional teams, including product, engineering, and business teams, to understand data needs and deliver solutions.
- Communicate findings and recommendations to stakeholders in a clear and concise manner.

Research and Development:
- Stay updated with the latest advancements in data science and data engineering.
- Experiment with new tools, techniques, and technologies to improve data processes and analytics.

Deployment and Maintenance:
- Deploy data pipelines and machine learning models into production and monitor their performance.
- Continuously improve and maintain existing data pipelines, data models and infrastructure.

Qualifications:
- Bachelors or Masters degree in Computer Science, Data Science, Statistics, Engineering, or a related field.

Experience:
- Minimum of 5 years industry experience in data science, data engineering, or a related field.
- Proven experience with data analysis, data engineering, data modeling, statistical modeling, and machine learning.

Technical Skills:
- Proficiency in programming languages such as Python, R, or Scala.
- Experience with data processing frameworks like Apache Spark, Hadoop, or similar.
- Strong SQL skills and experience with relational databases.
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
- Experience with data visualization tools like Tableau, Power BI, or similar.

The Hiring House jobs

Mid-Level Data Scientist / Engineer