Scikit-learn Developer

Vintti is a strategic staffing agency that enhances the competitiveness of US businesses. By connecting SMBs, startups, and firms with highly skilled Latin American professionals, we offer a cost-effective solution to talent acquisition. Our model allows companies to access top-tier expertise at rates that significantly reduce overhead costs, enabling businesses to allocate resources more efficiently and boost their bottom line.

A Scikit-learn Developer plays a crucial role in creating and implementing machine learning models using the Scikit-learn library, a powerful Python-based tool for data analysis and predictive modeling. These developers are adept at transforming raw data into actionable insights by utilizing various algorithms for classification, regression, clustering, and more. They work closely with data scientists and engineers to build and optimize models that solve real-world problems, ensuring high performance and scalability. Their expertise enables businesses to make data-driven decisions, improve processes, and drive innovation through advanced analytics.

- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
- Proven experience in developing machine learning models using Scikit-learn.
- Strong proficiency in Python programming language.
- Deep understanding of machine learning algorithms and principles.
- Experience with data preprocessing and feature engineering techniques.
- Familiarity with data manipulation libraries such as Pandas and NumPy.
- Strong debugging and problem-solving skills.
- Experience integrating machine learning models into production systems.
- Knowledge of software development best practices, including code versioning and documentation.
- Experience with unit testing and automated testing frameworks.
- Familiarity with other machine learning frameworks and libraries (e.g., TensorFlow, Keras) is a plus.
- Ability to write clean, efficient, and well-documented code.
- Strong communication skills and ability to collaborate with cross-functional teams.
- Experience with agile development methodologies.
- Ability to stay up-to-date with the latest advancements in Scikit-learn and related machine learning technologies.
- Strong analytical skills and attention to detail.
- Experience with cloud platforms (e.g., AWS, Google Cloud) is a plus.
- Proven ability to work independently and as part of a team.
- Experience mentoring junior developers is a plus.

- Design, develop, and optimize machine learning models using Scikit-learn.
- Collaborate with data scientists to define algorithm requirements and implementation strategies.
- Integrate Scikit-learn-based solutions into various applications and workflows.
- Perform preprocessing and feature engineering to prepare data for machine learning tasks.
- Troubleshoot and resolve issues in Scikit-learn code and related workflows.
- Enhance and maintain the performance and scalability of machine learning models.
- Conduct thorough code reviews to ensure high-quality code standards.
- Participate in agile development processes including daily stand-ups and planning sessions.
- Gather and clarify requirements from stakeholders and cross-functional teams.
- Develop unit tests and automated testing frameworks for machine learning models.
- Monitor the performance and accuracy of deployed machine learning models.
- Stay informed of advancements and updates in Scikit-learn and related tools.
- Create and maintain comprehensive documentation for code, models, and project developments.
- Provide training and mentorship to junior developers on best practices and coding standards.
- Collaborate with team members to ensure consistent application of best practices and coding standards.

The ideal candidate for the Scikit-learn Developer role is a highly skilled and motivated professional with a Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field. They have proven experience in developing and optimizing machine learning models using Scikit-learn, coupled with strong proficiency in Python programming and a profound understanding of machine learning algorithms and principles. Their expertise extends to data preprocessing and feature engineering, as well as fluency in data manipulation libraries such as Pandas and NumPy. The candidate demonstrates exceptional debugging and problem-solving skills and has practical experience in integrating machine learning models into production systems. They adhere to software development best practices, including code versioning and documentation, and possess a familiarity with unit testing and automated testing frameworks. While proficiency in other machine learning frameworks is an advantage, their ability to write clean, efficient, and well-documented code stands out. This professional is a strong communicator, effectively collaborating with cross-functional teams and stakeholders. They thrive in agile development environments and showcase excellent analytical skills, attention to detail, and a proactive, self-motivated attitude towards learning new technologies. Additionally, experience with cloud platforms and mentorship capabilities are desirable attributes. They exhibit strong organizational skills, a commitment to high-quality coding standards, and a dedication to continuous improvement and professional development, making them a valuable and dynamic addition to the team.

- Develop, test, and maintain software using Scikit-learn for machine learning applications.
- Collaborate with data scientists to design and implement machine learning algorithms.
- Write clean, efficient, and well-documented code.
- Integrate Scikit-learn models into existing systems and workflows.
- Perform data preprocessing and feature engineering for model training.
- Debug and resolve issues related to Scikit-learn code and workflows.
- Optimize machine learning models for performance and scalability.
- Conduct code reviews and provide constructive feedback to team members.
- Participate in daily stand-ups and agile planning sessions.
- Collaborate with cross-functional teams to gather requirements and clarify project objectives.
- Develop and maintain unit tests for machine learning models.
- Monitor and evaluate the performance of deployed models.
- Stay up-to-date with the latest developments in Scikit-learn and related technologies.
- Document project progress, code changes, and technical decisions.
- Assist in mentoring junior developers on best practices in machine learning development.

- Strong analytical and problem-solving mindset.
- Excellent written and verbal communication skills.
- Team-oriented with a collaborative spirit.
- High attention to detail and precision.
- Proactive and self-motivated with a strong work ethic.
- Adaptable and open to learning new technologies and methodologies.
- Ability to manage and prioritize multiple tasks efficiently.
- Innovative thinker with the ability to find creative solutions to complex problems.
- Strong organizational skills and ability to maintain detailed documentation.
- Commitment to continuous improvement and professional development.
- High level of professionalism and integrity.
- Capable of mentoring and supporting team members.
- Strong competences in time management and deadline adherence.
- Enthusiastic about staying current with industry trends and developments.
- Dedicated to maintaining high-quality coding standards and practices.
- Open to constructive feedback and committed to refining skills and approaches.
- Sensitive to the needs and requirements of both technical and non-technical stakeholders.

- Competitive salary range based on experience and qualifications.
- Comprehensive health, dental, and vision insurance plans.
- Flexible work hours and remote work options.
- Generous paid time off and holidays.
- Professional development opportunities and access to training programs.
- Performance-based bonuses and incentives.
- Retirement savings plan with company matching contributions.
- Access to state-of-the-art technology and tools.
- Employee wellness programs and resources.
- Supportive and inclusive work culture.
- Unlimited access to online learning platforms and resources.
- Participation in industry conferences and events.
- Collaborative and innovative work environment.
- Opportunities for career advancement and promotions.
- Employee assistance program for personal and professional support.
- Regular team-building activities and social events.
- Subsidized gym memberships and fitness programs.
- Monthly or quarterly tech allowance for home office setup.
- Company-sponsored hackathons and innovation challenges.