Data Scientist & Engineer role

The Data Scientist and Engineer role reports to the Chief Data Officer (CDO) and is part of the Data Team, which focuses on managing and using data to support decision-making. You’ll contribute to improving data capabilities, work on varied projects, collaborate with teams across the company, and help shape our data strategy. It’s a high-impact role with strong opportunities for growth and development.

Responsibilities

·       Data pipeline development and management: Design, build, and maintain robust and scalable ETL/ELT data pipelines from diverse sources.

·       Data quality & governance: Ensure data quality, integrity, and governance and automate all QC processes. Implement and uphold data security, privacy, and compliance standards.

·       Monitoring and alerting: Implement monitoring and alerting systems for data pipelines and models to ensure reliability, performance and a cost-efficient architecture.

·       Prescriptive modeling: Build and deploy ML models to specify the next best actions (NBAs) per client and lead.

·       AI pipeline development and automation: Create and maintain robust MLOps pipelines for efficient model deployment and management.

·       Stakeholder collaboration: Work closely with business stakeholders to understand their data needs and translate them into technical requirements.

·       Documentation and knowledge sharing: Create and maintain comprehensive documentation of data processes, models, and insights for knowledge sharing across the organization.

Requirements

·      3-7 years of professional experience in data science/engineering roles.

·       BSc and MSc / PhD degree in computer science, statistics, or related technical field.

·       Demonstrated experience delivering end-to-end data science/engineering projects.

Data skills:

·       Strong proficiency in Python for data analysis and machine learning

·       Experience building and managing ETL pipelines on cloud platforms (GCP preferred)

·       Experience with data analysis libraries like pandas, NumPy, and scikit-learn

·       Expertise in building and deploying machine learning and AI models

·       Knowledge of deep learning frameworks such as TensorFlow or PyTorch

·       Experience with big data technologies such as Spark

·       Proficiency in SQL and working with relational databases

·       Familiarity with data lakes and lakehouses (BigQuery preferred)

·       Experience with version control using Git

Cloud skills:

·       Hands-on experience with GCP for data and ML workflows

·       Familiarity with serverless computing (e.g. Google Cloud Functions)

Soft skills:

·       Strong analytical and problem-solving abilities

·       Excellent communication skills to present findings to technical and non-technical audiences

·       Ability to work independently and as part of a team

·       Solution oriented,

·       Attention to detail

·       Always seeking to grow, learn, and drive the business forward

Additional desired :

·       Experience with containerization and orchestration (Docker, Kubernetes)

·       Knowledge of data streaming technologies (e.g. Kafka)

·       Familiarity with NoSQL databases

·       Understanding of data privacy and security best practices

Benefits

What’s in it for you:

·        Work in a fast-paced environment at a leading, trend-setting company with pioneer products.

·        Competitive remuneration, based on your skills and experience.

·        Ongoing learning opportunities and free participation in BOUSSIAS events and conferences