We are seeking a highly skilled and innovative Software Engineer with Data Science knowledge to join our dynamic team. The ideal candidate will have a strong background in both software/data engineering and knowledge of data science is preferable. This role will involve developing and maintaining software applications, building and optimizing scalable data pipelines, and implementing data science/ AI solutions to enhance our marketing strategies and customer experiences.

Key Responsibilities:

Implement full software development process (React preferred)
Work with data streams and APIs to provide enhanced automation capabilities.
Develop flowcharts, layouts, and documentation to identify requirements and solutions.
Gather user requirements and technical requirements.
Write well-designed, testable code.
Automate and scale data pipelines with data engineers to support marketing analytics.
Implement generative AI solutions to enhance marketing workflows. Stay current with AI/ML advancements and prototype innovative solutions.
Collaborate with cross-functional teams to gather requirements and translate them into technical specifications.
Ensure compliance with data privacy regulations and implement best practices in data management and governance.

Requirements:

Min 5+ years of experience with Bachelor's degree in Computer Science, Data Science, or a related STEM field. knowledge of using agile software development techniques. Excellent interpersonal skills and an eagerness to collaborate.
Frontend Technologies: Proficiency in HTML, CSS, and JavaScript, along with frameworks like React or Angular.
Backend Technologies: Strong knowledge of Node.js, Python, or Java, and experience with backend frameworks such as Express.js or Django.
Docker: Experience with Docker for containerization, including creating and managing Docker containers, Docker Compose, and Docker Swarm.
Database Management: Proficiency in SQL (knowledge of NoSQL databases is advantage) and experience with data warehousing solutions such as Azure Synapse Analytics2.
Cloud Platforms: Knowledge of Azure Databricks cloud services preferred, specifically services related to data storage, processing, and deployment.
Version Control: Proficiency in using Git and GitHub for version control and collaboration.

Good to have-

Familiarity with ML frameworks (scikit-learn, TensorFlow, PyTorch) and MLOps practices.
Knowledge of large language models (LLMs) and generative AI technologies.
DevOps: Understanding of CI/CD pipelines, and experience with tools like Jenkins, GitLab CI, or Azure DevOps.

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