Coderio designs and delivers scalable digital solutions for global companies. We combine strong technical expertise with a product mindset to lead complex software initiatives end-to-end. We work with international clients, value autonomy and clear communication, and build long-term partnerships through technical excellence.
More information: http://coderio.com
We are looking for a Senior Data Scientist Lead to join one of our international clients and lead the design, development, and delivery of data science solutions that generate measurable business value.
This is a high-impact technical leadership role for an experienced Data Scientist who combines strong hands-on expertise with the ability to guide technical decisions, mentor other data professionals, and collaborate with business and engineering stakeholders.
You will work across the full data science lifecycle, from understanding business problems and defining analytical approaches to developing machine learning models, deploying solutions to production, and continuously improving their performance.
The ideal candidate is highly analytical, hands-on, business-oriented, and comfortable working with cloud-based data and machine learning environments, particularly AWS.
Data Science Leadership: Lead the design and implementation of data science initiatives, defining methodologies, technical approaches, and best practices across projects.
Machine Learning & Modeling: Develop, evaluate, and optimize statistical and machine learning models to solve complex business problems and generate actionable insights.
End-to-End Data Science: Own the complete data science lifecycle, including data exploration, feature engineering, model development, validation, deployment, monitoring, and continuous improvement.
AWS & Cloud Solutions: Design and implement scalable data science and machine learning solutions leveraging AWS cloud services and best practices.
Technical Leadership: Provide technical guidance to Data Scientists and other technical team members, promoting high-quality engineering and analytical practices.
Business Collaboration: Work closely with business stakeholders, product teams, data engineers, and software engineers to translate business challenges into effective data-driven solutions.
Model Performance & Optimization: Monitor model performance, identify opportunities for improvement, and ensure solutions remain accurate, scalable, and aligned with business objectives.
Data Strategy: Contribute to the definition of data science strategies, analytical frameworks, and best practices that support long-term business growth.
Knowledge Sharing: Mentor team members, conduct technical reviews, and promote knowledge sharing across the organization.
Experience: 6+ years of professional experience in Data Science, Machine Learning, Advanced Analytics, or a related field, with proven experience leading technical initiatives or teams.
Data Science Expertise: Strong hands-on experience with statistical modeling, machine learning algorithms, predictive analytics, experimentation, and data-driven problem solving.
Programming: Advanced proficiency in Python, with experience using common data science and machine learning libraries such as Pandas, NumPy, Scikit-learn, or similar.
Machine Learning: Strong understanding of supervised and unsupervised learning, model evaluation, feature engineering, optimization, and production machine learning practices.
AWS: Solid hands-on experience designing or implementing data science and machine learning solutions in AWS environments.
Data & SQL: Strong SQL skills and experience working with large datasets, data warehouses, and complex data environments.
Technical Leadership: Proven ability to lead technical discussions, make architecture and modeling decisions, mentor other professionals, and drive projects from concept to production.
Communication: Advanced English proficiency, with the ability to communicate complex technical concepts clearly with international teams, stakeholders, and leadership.
Problem Solving: Strong analytical and critical-thinking skills, with a pragmatic approach to solving complex business and technical challenges.
Experience with AWS services such as SageMaker, S3, Glue, Redshift, Lambda, EMR, or Athena.
Experience deploying and monitoring machine learning models in production.
Experience with MLOps and ML lifecycle automation.
Experience with Spark or other distributed data processing frameworks.
Experience with Docker and Kubernetes.
Experience with Generative AI, LLMs, RAG, or NLP solutions.
AWS certifications related to Data, Machine Learning, or Solutions Architecture.
Experience working in financial services or other data-intensive industries.
100% remote work.
Long-term engagement with international clients.
High-impact technical leadership role.
Opportunity to influence data science and machine learning strategy.
Collaborative international environment with experienced technical teams.
Continuous learning and professional growth opportunities.
At Coderio, we value talent regardless of location. We are a fully remote company, passionate about technology, collaboration, and technical excellence. We offer an inclusive and challenging environment where experienced professionals can take ownership, influence technical strategy, and work on meaningful projects with global clients.
If you are an experienced Data Scientist who enjoys combining hands-on technical work with leadership, mentoring, and business impact, we'd love to hear from you.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
