Data Scientist

TytoCare; Lisboa; Presencial; EUR 40 000 - 60 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid mode of work

Flexible schedule

Healthcare benefits

Fully-stocked kitchens

Benefits package

Wellness program

Team events

Global onboarding

Full access to Udemy

Resumo da oferta

Phiture in Lisbon is seeking a Data Scientist to join its Data Science department. The ideal candidate will have 3+ years of experience in machine learning and a strong proficiency in Python and SQL. The role involves data exploration, statistical analysis, and collaborative problem-solving. Phiture offers a hybrid mode of work, a flexible schedule, and a comprehensive benefits package, including healthcare, wellness programs, and personal development opportunities.

Qualificações

• 3+ years of proven experience designing and implementing machine learning algorithms.
• Strong understanding and practical experience with various machine learning algorithms.
• Solid foundation in statistical concepts and techniques.

Responsabilidades

• Collect, clean, and transform large data sets for analysis.
• Develop and implement machine learning algorithms.
• Build, train, and optimize machine learning models.

Conhecimentos

Machine Learning

Data Analysis

Python

Data Visualization

SQL

Formação académica

B.Sc in Computer Science, Mathematics, Statistics, or related field

Ferramentas

Pandas

NumPy

Airflow

CircleCI

PySpark

Docker

Kubernetes

Descrição da oferta de emprego

About the Role

*** A third party will recruit, hire, and employ this position.

The Data Science department plays a pivotal role in our company, generating value to Riskified by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.

What You'll Be Doing

• Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
• Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
• Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
• Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
• Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
• Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
• Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
• Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

Qualifications

• B.Sc (M.Sc is a plus) in Computer Science, Mathematics, Statistics, or a related field
• 3+ years of proven experience designing and implementing machine learning algorithms and successfully deploying them to production.
• Strong understanding and practical experience with various machine learning algorithms.
• Proficiency in Python, Experience with SQL and data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform data for analysis
• Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design
• Strong analytical and critical thinking skills to approach business problems, formulate hypotheses, and translate them into actionable solutions
• Proficiency in data visualization libraries, to create meaningful visual representations of complex data
• Excellent written and verbal communication skills to present complex findings and technical concepts to both technical and non-technical stakeholders
• Demonstrated ability to work effectively in cross‑functional teams, collaborate with colleagues, and contribute to a positive work environment

Advantages

• Experience in the fraud domain
• Experience with Airflow, CircleCI, PySpark, Docker and K8S

Benefits

• Hybrid mode of work
• Flexible schedule
• Healthcare benefits
• Fully‑stocked kitchens
• Benefits package per month—per your choice, e.g., work‑from‑home equipment, gym membership, wellbeing activities, and more.
• Wellness program
• Celebrations and activities
• Team events
• Happy hours
• Awesome Riskified gifts and swags
• Volunteer programs
• Personal development
• Global onboarding
• Role‑based technical skills training
• Full access to Udemy

Riskified is deeply committed to the principle of equal opportunity for all individuals. We do not discriminate based on race, color, religion, sex, sexual orientation, national origin, age, disability, veteran status, or any other status protected by law.