Data Scientist

Data Scientist-PortugalRemote but must live in Portugal

About Tillster

Are you a passionate data scientist with a knack for data?

Job Description:

Responsibilities:

• Drive the design, development, and deployment of machine learning models, with an emphasis on the Recommender System, ensuring scalability and robustness for handling large datasets and multiple clients.
• Collaborate with data engineers and ML engineers to implement MLOps best practices, ensuring seamless integration of models into production pipelines, including both batch and real-time predictions, automated model retraining, versioning, and monitoring.
• Oversee the operationalization of models, including real-time predictions, batch processing, and retraining pipelines, especially for the Recommender System.
• Monitor model performance post-deployment, implementing metrics and alerts to track model drift, accuracy degradation, and data changes.
• Build and maintain continuous integration (CI) and continuous deployment (CD) pipelines to ensure models are rapidly and reliably updated in production.
• Ensure the model serving infrastructure is optimized for performance, resource utilization, and cost efficiency, leveraging GCP.
• Work closely with product managers and stakeholders to define and refine ML model objectives, translating business needs into model requirements.
• Implement automated testing, validation, and documentation of models to ensure they meet performance and accuracy standards before deployment.
• Act as a key technical advisor on AI and ML initiatives, working with the team to share best practices in AI, MLOps, and model deployment, while contributing to the AI-powered decision-making systems to integrate customer data with external factors (e.g., weather, location, and time of day).
• Use Large Language Models (LLMs), such as Gemini, to enhance and develop AI-driven features within our platform.
• Work collaboratively with cross-functional teams, ensuring teamwork and communication are key aspects of problem-solving and project success.

Required Skills:

• Bachelor’s or Master’s degree in a quantitative discipline such as Data Science, Computer Science, Engineering, or a related field;.
• Minimum of 5+ years of experience as a Data Scientist, with at least 2+ years of experience in MLOps and ML model deployment at scale.
• Proven expertise in deploying machine learning models for large-scale production environments and monitoring their performance for multiple clients or business units.
• Hands-on experience with MLOps tools such as Airflow, and cloud-based solutions (GCP Vertex AI).
• Proficiency in Python for deep learning model development and deployment (mandatory).
• Proven experience with Deep Learning and Reinforcement Learning for building machine learning models at scale (mandatory).
• Experience with NoSQL databases (e.g., MongoDB) and JSON for handling Big Data and real-time applications.
• Experience working with Recommender Systems.
• Experience working with TensorFlow Recommender System (TFRS) and Two Towers architecture is a plus.
• Experience with model monitoring, performance tracking, and A/B testing in production environments to ensure continuous improvement and accuracy.
• Expertise in implementing scalable and automated CI/CD pipelines for machine learning models, including model versioning and retraining workflows.
• Strong knowledge of containerization and orchestration tools such as Docker and Kubernetes.
• Experience working with Large Language Models (LLMs), such as Gemini or ChatGPT-4, to build intelligent systems (mandatory).
• Understanding of data engineering concepts, including ETL pipelines, data lakes, and big data platforms (BigQuery, Snowflake, Redshift).
• Strong teamwork and collaboration skills, with a focus on working across departments to achieve project success.

• Experience with multi-tenant ML platforms, serving models to multiple clients with different data and needs (preferred).
• Familiarity with DevOps and cloud infrastructure, especially utilizing serverless technologies such as GCP Functions or AWS Lambda.
• Experience working with natural language processing (NLP) or computer vision models in production.

Thriving at Tillster

Put Customers First:

Collaborate: 

Innovate: 

Operate from Data: 

Drive Results: 

Own It: 

Be Passionate and Have Fun: 

The Interview Process

Making a Difference in the Tillster Way

Follow us on:

Pay and Benefits (PORTUGAL)

• Compensation competitive to market and geographical location.
• Meal allowance for each day worked available through meal card.
• Home/Office allowance reimbursement per calendar month, pro-rated based on employment start date.
• Health insurance: Tillster pays the premium for employee private health insurance. Employees have the option to add their spouse/dependents at the employee’s cost.
• Holidays: Up to 20 federal and local/municipal holidays in accordance with applicable Portuguese Labour laws, dependent on your employment start date.
• Vacation: Up to 22 days of vacation every holiday year, pro-rated based on employment start date.
• Education, Learning & Development: We offer Udemy Learning courses; and ongoing learning and development opportunities.

Tillster is proudly an Equal Opportunity Employer

No Visa Sponsorship

Principals only – no Agencies or calls please

About Tillster

Thriving at Tillster

• Put Customers First: Prioritize the needs and satisfaction of our customers in all decisions and actions appropriate to Tillster’s stage of development, resources, and stated goals.
• Collaborate: Work together effectively, leveraging diverse perspectives to achieve common goals.
• Innovate: Embrace creativity and pursue new ideas to drive progress and improvement.
• Operate from Data: Use strong critical thinking skills to make informed decisions based on accurate and relevant data.
• Drive Results: Focus on achieving tangible outcomes and delivering high performance.
• Own It: Take responsibility for your actions and the success of your work.
• Be Passionate and Have Fun: Bring enthusiasm to your work and enjoy the journey.

Making a Difference in the Tillster Way

Follow us on: Tillster.com: https://www.tillster.com/ Tillster Careers: https://www.tillster.com/careers LinkedIn: https://www.linkedin.com/company/tillster/