Data Science Researcher

Vintti is a staffing agency dedicated to boosting the economic efficiency of US companies. We provide access to a diverse range of skilled Latin American professionals, allowing businesses to build robust teams without the traditional high costs associated with domestic hiring. Our model supports companies in maximizing their resources, driving innovation, and achieving sustainable growth.

A Data Science Researcher is a pivotal role in the realm of data analytics and machine learning. This position involves exploring and analyzing large datasets to uncover patterns, trends, and insights that drive decision-making and innovation. By employing statistical techniques, machine learning models, and data visualization tools, Data Science Researchers develop and validate hypotheses, solve complex problems, and contribute to the advancement of knowledge in various domains. This role requires a blend of analytical prowess, programming skills, and domain expertise to transform raw data into actionable intelligence and foster data-driven strategies.

- Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field
- Proven experience as a Data Science Researcher or in a similar role
- Proficiency in statistical analysis and machine learning techniques
- Strong programming skills in languages such as Python, R, or similar
- Experience with data visualization tools like Tableau, PowerBI, or Matplotlib
- Knowledge of SQL and database management
- Hands-on experience with cloud computing platforms such as AWS, Azure, or Google Cloud
- Familiarity with big data processing tools like Spark, Hadoop, or similar
- Strong understanding of data preprocessing and feature engineering
- Excellent problem-solving and critical-thinking skills
- Strong analytical and quantitative skills
- Ability to design experiments and interpret results
- Demonstrated ability to develop scalable and efficient data pipelines
- Excellent communication skills to present findings to technical and non-technical stakeholders
- Experience with version control systems like Git
- Ability to work collaboratively in a team environment
- Strong organizational skills and attention to detail
- Knowledge of advanced topics such as deep learning, natural language processing, or reinforcement learning is a plus
- Experience in mentoring junior team members is desirable
- Demonstrated ability to stay up-to-date with industry trends and advancements in data science technologies

- Analyze and interpret complex data sets to derive valuable insights
- Develop machine learning models and algorithms for predictive analytics
- Perform experiments to validate the accuracy and efficiency of developed models
- Collaborate with cross-functional teams to translate business requirements into data solutions
- Clean, preprocess, and ensure the integrity of data for analysis
- Create and maintain data pipelines for consistent and reproducible data processing
- Communicate analytical findings through reports and visualizations to stakeholders
- Stay current with advancements in data science methodologies and tools
- Optimize and fine-tune algorithms for performance and scalability in production systems
- Conduct exploratory data analysis to identify trends, patterns, and anomalies
- Participate in code reviews to maintain high-quality code standards
- Contribute to technical documentation of models, processes, and workflows
- Develop prototypes to demonstrate the feasibility of advanced analytics solutions
- Mentor junior data scientists and analysts in technical skills and best practices
- Collaborate with peers to brainstorm and refine analytical approaches
- Automate data processing and analysis tasks to enhance efficiency and reduce manual effort

The ideal candidate for the Data Science Researcher role is a seasoned professional with a robust educational background in Data Science, Statistics, Mathematics, Computer Science, or a closely related field, holding at least a Bachelor's degree, with a Master’s or higher being preferred. They possess proven experience in a similar role, showcasing strong proficiency in statistical analysis and machine learning techniques. Their expertise includes advanced programming skills in languages such as Python or R, and they are adept with data visualization tools like Tableau, PowerBI, or Matplotlib, as well as SQL and database management. They are well-versed in cloud computing platforms such as AWS, Azure, or Google Cloud and have hands-on experience with big data processing tools like Spark or Hadoop. This candidate is not only technically proficient, with a deep understanding of data preprocessing and feature engineering, but also exhibits excellent problem-solving, analytical, and quantitative skills. They are capable of designing experiments and interpreting results with precision, developing scalable data pipelines, and performing exploratory data analysis to uncover trends and patterns. Strong communication skills enable them to effectively present complex findings to both technical and non-technical stakeholders. They are an innovative thinker who is proactive in seeking novel solutions and maintaining high standards of work. Their ability to collaborate effectively within cross-functional teams, mentor junior members, and manage multiple tasks with strong organizational skills sets them apart. A lifelong learner with a passion for data science, they stay current with industry trends and advancements. The ideal candidate is not only technically skilled but also embodies personal attributes such as reliability, resilience, ethical integrity, and a genuine enthusiasm for applying data science to solve real-world business challenges.

- Analyze and interpret complex data sets using statistical and machine learning methods
- Develop predictive models and algorithms to address business challenges
- Design and perform experiments to validate model accuracy and efficiency
- Collaborate with cross-functional teams to understand data needs and deliver actionable insights
- Clean, preprocess, and verify the integrity of data used for analysis
- Create and maintain scalable, reliable, and reproducible data pipelines
- Communicate results and findings to stakeholders through visualizations and reports
- Stay updated with the latest industry trends, tools, and technologies in data science
- Optimize and tune algorithms for performance and scalability in production environments
- Conduct exploratory data analysis to discover trends and patterns
- Participate in code reviews and contribute to technical documentation
- Develop prototypes and proof-of-concepts to demonstrate the utility of advanced analytics
- Mentor and provide guidance to junior data scientists and analysts
- Engage in peer collaboration to brainstorm and challenge assumptions
- Automate repetitive tasks to improve efficiency and eliminate manual work

- Analytical mindset with strong problem-solving skills
- Passion and curiosity for uncovering patterns and insights from data
- Detail-oriented with a commitment to precision and accuracy
- Proactive and self-motivated in pursuing innovative solutions
- Excellent communicator, able to convey complex concepts clearly
- Team player who thrives in a collaborative environment
- Ability to think creatively and approach problems from multiple angles
- Strong organizational skills and ability to manage multiple tasks simultaneously
- Adaptable and resilient in the face of evolving priorities and challenges
- Lifelong learner, eager to stay updated with the latest advancements in data science
- Results-driven with a focus on delivering actionable insights and measurable impact
- Technically proficient with a solid foundation in data science methodologies and tools
- Able to mentor and support the development of junior team members
- Persistent and determined, capable of working through complex challenges
- Innovative, with a penchant for developing new approaches and solutions
- Reliable and consistent in maintaining high standards of work
- Strong ethical standards and a commitment to data integrity
- Ability to work independently while also contributing to team goals
- Enthusiastic about applying data science to solve real-world business problems
- Attention to detail with a commitment to producing high-quality work

- Competitive salary ranging from $100,000 to $150,000 based on experience
- Comprehensive health, dental, and vision insurance plans
- Generous paid time off and holidays
- Flexible work hours and remote work options
- 401(k) retirement plan with company matching
- Professional development and continuous learning opportunities
- Access to industry conferences and workshops
- Employee wellness programs including gym memberships and mental health support
- Opportunities for career advancement and promotion
- Collaborative and inclusive work environment
- Performance-based bonuses and incentives
- Stock options or equity participation
- Paid parental leave and family support benefits
- Tuition reimbursement for further education
- Subscription to online learning platforms like Coursera and Udacity
- Company-sponsored social events and team-building activities
- Assistance with immigration and visa processes, if applicable
- State-of-the-art office facilities with modern amenities