Principle Software Engineer - Data Science Job Description Template
As a Principle Software Engineer - Data Science, you will lead the development and implementation of sophisticated data science models and algorithms, working closely with stakeholders to solve complex business challenges. Your expertise will drive the innovation and efficiency of our data-driven strategies.
Responsibilities
- Architect, design, and implement advanced data science models and algorithms.
- Lead and mentor a team of software engineers and data scientists.
- Collaborate cross-functionally with stakeholders to understand business requirements.
- Conduct code reviews and ensure adherence to best practices in software engineering.
- Identify and integrate new data sources to enhance model performance.
- Optimize and scale machine learning models for real-time processing.
- Stay up-to-date with the latest advances in data science and software engineering.
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
- 10+ years of experience in software engineering and data science.
- Proven track record of leading high-performing teams.
- Strong knowledge of machine learning frameworks and big data technologies.
- Excellent problem-solving and analytical skills.
- Experience with cloud platforms such as AWS, GCP, or Azure.
Skills
- Python
- R
- Apache Spark
- TensorFlow
- PyTorch
- SQL
- AWS
- Kubernetes
- Docker
- Machine Learning
- Deep Learning
- Big Data
- Data Mining
Frequently Asked Questions
A Principle Software Engineer in Data Science leads complex data-driven projects, devises algorithms, and implements machine learning models. They bridge software engineering with data science to create scalable solutions, collaborate with cross-functional teams, and manage large datasets, also ensuring data integrity and performance optimization.
To become a Principle Software Engineer in Data Science, one typically needs a strong foundation in computer science, mastery in programming languages like Python or Java, and expertise in data science techniques. Usually, a bachelor's or master's degree in a related field plus extensive experience in software engineering and data projects is required.
The average salary for a Principle Software Engineer in Data Science varies based on location, experience, and organization size. Salaries are generally higher due to the seniority and specialized skills required, encompassing both software engineering and data science expertise to solve complex technological challenges.
A Principle Software Engineer in Data Science typically needs a degree in computer science, data science, or a related field, along with significant experience in software development and data analysis. Proficiency in programming languages, machine learning, statistics, and big data technologies is also essential for this senior role.
Key skills for a Principle Software Engineer in Data Science include leadership, advanced programming, data modeling, and machine learning expertise. Responsibilities include designing data architectures, leading project teams, integrating data solutions into software frameworks, and staying abreast of emerging technologies to drive innovation.