Data Engineer / Scientist

o We are seeking a passionate and innovative Data Engineer/Scientist to join our IT organization as part of a dynamic cross-functional team. In this role, you will build and maintain the data infrastructure required for AI/ML models, ensuring data is easily accessible, clean, and organized for downstream tasks. You will also develop AI models, perform data analysis, and turn data insights into actionable business strategies. Additionally, you will work with business stakeholders to identify use cases, analyze data, and develop insights and predictive models.

Key Responsibilities:

o Data Infrastructure Development and Maintenance:

Build and maintain data pipelines and infrastructure to collect, process, and make data accessible for AI/ML models, other projects and colleagues.

Design and implement data pipelines using ETL tools (e. g., Azure Data Factory, Apache Spark, Databricks).

Manage and optimize data storage solutions (e. g., Azure Data Lake, Synapse Analytics).

Ensure data quality, consistency, and security by creating monitoring mechanisms to ensure the quality, and notice issues proactively.

o AI Model Development and Data Analysis:

Develop AI models, perform data analysis, and turn data insights into actionable business strategies.

Conduct exploratory data analysis (EDA) to uncover trends and patterns, and document them.

Work on feature engineering, model selection, and validation in a structured manner using scientific approach.

Interpret model outputs and communicate results to non-technical stakeholders.

Good communication skills and excellent story telling of data analysis results

Identify bottlenecks and inefficiencies in processes through data analysis

Recommend and implement process improvements based on data driven insights

o Collaboration and Stakeholder Engagement:

Work with business stakeholders to identify use cases, analyze data, and develop insights and predictive models.

Collaborate with the data team to define data requirements for model training and evaluation.

Engage with business teams to understand their needs and deliver data solutions that add tangible value..

Communicate complex data concepts and the benefits of data projects to non-technical stakeholders effectively.

Required Qualifications:

o Bachelors or masters degree in Computer Science, Data Science, Engineering, or a related field, with 6-9 years of IT experience, including a minimum of 3-5 years of relevant experience as Data Engineer/Scientist.

o Proficiency in SQL, Python, and data pipeline tools, spark would be an advantage.

o Experience with cloud data storage solutions (Azure, AWS, Google Cloud).

o Understanding of data governance and compliance requirements.

o Strong knowledge of LLM, SLM, machine learning algorithms and best practices.

o Good understanding of Hierarchical Multi-Agent systems

o Ability to translate complex analyses into actionable insights.

o Proficiency in Python, R, and statistical analysis.

o Experience in data visualization frameworks such as Plotly and Dash

o Good understanding of RAG concept and experience in documentation

o Solid understanding of natural language processing approach and analysis

o Familiarity with libraries such as langchain, pytorch, langgraph, pandas, numpy, scikit-learn, mlflow

Preferred Qualifications:

o Experience in developing data solutions for marketing, sales, or communications.

o Knowledge of cloud services (AWS, Azure, Google Cloud) and their data offerings.

o Demonstrated ability to work in cross-functional teams and manage projects.

o Familiarity with agile development methodologies.