Senior Data Scientist

Descompagnons Trabalho Temporário Lda; Lisboa; Presencial; EUR 40 000 - 60 000; Tempo integral

Resumo da oferta

A leading cloud automation company based in Lisbon is seeking a dynamic Senior Data Scientist to drive operational excellence through data. You will develop sophisticated machine learning models and collaborate with cross-functional teams. Ideal candidates have over 5 years of experience in data science, strong technical skills, and a proven track record of impactful projects. This role offers a competitive salary, equity options, and the chance to work in a fast-paced, innovative environment.

Serviços

Competitive salary

Equity options

Transparent work environment

Focus time with minimal meetings

Qualificações

• 5+ years of experience in data science and machine learning.
• Experience in training tabular and time series models.
• Proficient in building data pipelines and conducting experiments.

Responsabilidades

• Create, validate, and maintain machine learning algorithms.
• Design, execute, and evaluate experiments to refine models.
• Perform in-depth data analysis and deliver actionable insights.

Conhecimentos

Data Science

Machine Learning

SQL

Analytical Skills

Communication Skills

Ferramentas

AWS

Azure

GCP

Kubernetes

MLflow

BigQuery

Snowflake

Descrição da oferta de emprego

Cast AI is the leading Application Performance Automation (APA) platform, enabling customers to cut cloud costs, improve performance, and boost productivity – automatically. Built originally for Kubernetes, Cast AI goes beyond cost and observability by delivering time, autonomous optimization across any cloud environment. The platform continuously analyzes workloads, rightsizes resources, and rebalances clusters without manual intervention, ensuring applications run faster, more reliably, and more efficiently. Headquartered in Miami, Florida, Cast AI has employees in more than 32 countries worldwide and supports some of the world’s most innovative teams running their applications on all major cloud, hybrid, and premises environments. Over 2, 100 companies already rely on Cast - from BMW and Akamai to Hugging Face and Nielsen IQ. What’s next? Backed by our $108M Series C, we’re doubling down on making APA the new standard for Dev Ops and MLOps, and everything in between.

Core values that hold us all together:

PRACTICE CUSTOMER OBSESSION. Focus on the customer journey and work backwards. Strive to deliver customer value and continuously solve customer problems. Listen to customer feedback, act, and iterate to improve customer experience.

LEAD. Take ownership and lead through action. Think and act on behalf of the entire company to build term value across team boundaries.

DEVELOP AND HIRE THE BEST. Strive to raise the performance bar by continuously investing in yourself, the team and by hiring the best possible candidates for every position. Drive towards personal development and professional growth, and mentor others to raise the collective bar.

EXPECT AND ADVOCATE CHANGE. Strive to innovate and accept the inevitable change that comes with innovation. Constantly welcome new ideas and opinions. Share insights responsibly with unwavering openness, honesty, and respect. Once a path is chosen, be ready to disagree and commit to a direction.

Role overview

We are seeking a dynamic and innovative Senior Data Scientist to join our thinking team. In this pivotal role, you will leverage data to drive operational excellence and spearhead the development of sophisticated machine learning models. Collaborate with tier Machine Learning and Data Engineers to bring these models into production and provide AI expertise across the organization, ensuring driven making and innovative solutions.

Responsibilities

• Develop Machine Learning Models: Create, validate, and maintain machine learning algorithms, focusing on both tabular and time series data.
• Run Data Science Experiments: Design, execute, and evaluate experiments to refine models and improve outcomes.
• Analyze Data: Perform dive data analysis and deliver actionable insights to shape our business strategies.
• Collaborate: Work closely with functional teams to align data science projects with company goals.
• Stay Current: Keep up with the latest advancements in data science, cloud technologies, and Dev Ops.
• Master Databases: Write, debug, and optimize complex SQL queries while effectively navigating OLAP and OLTP systems.

Requirements

• Experience: 5+ years of on experience in data science and machine learning, with a proven portfolio of impactful projects.
• Modelling Expertise: Experience in training tabular and series models using classical machine learning and deep learning approaches.
• Technical Skills: Proficiency in building data pipelines, training models, and conducting experiments using standard tools.
• Database Knowledge: Advanced SQL skills, including the ability to debug complex queries and a solid understanding of OLTP vs. OLAP systems (experience with OLAP systems is a plus).
• Problem-Solving: Exceptional analytical skills with an oriented and innovative approach to challenges.
• Communication: Strong verbal and written communication skills to collaborate effectively within a team.

Bonus points

• Cloud & Containers: Experience with cloud platforms (AWS, GCP, Azure) and container tools like Kubernetes.
• ML Pipelines: Expertise in ML pipeline development, including data preprocessing, model training, deployment, and monitoring.
• MLOps Tools: Familiarity with MLOps tools like MLflow or Feast.
• OLAP Expertise: Hands‑on experience with scale OLAP systems such as Clickhouse, BigQuery, or Snowflake.
• Advanced Modeling: Knowledge of advanced techniques for handling imbalanced datasets and other complex modeling challenges.

What's in it for you

• Competitive salary (€6,500 - €9,000 gross, depending on the level of experience) with equity options.
• Direct impact on the product in a edge company that’s reshaping cloud automation and optimization.
• Collaborate with a global team of top cloud experts and innovators passionate about pushing the boundaries of Kubernetes technology.
• Fast development cycles with a short feedback loop and direct customer impact.
• Transparent work environment.
• Focus time with minimal meetings and bureaucracy.
• 10% of your time dedicated to improvement and personal projects.