Data Scientist (AI and Deep Learning)

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 Scientist (AI and Deep Learning) leverages advanced analytics and machine learning techniques to derive actionable insights from large datasets. This role involves developing complex models and algorithms that allow for predictions and decision-making automation. Utilizing tools such as neural networks and deep learning frameworks, the Data Scientist works to solve intricate problems and improve systems performance across a variety of applications. They collaborate with cross-functional teams to implement AI solutions, ensuring they align with organizational objectives and drive innovation. Their work is pivotal in transforming data into strategic assets, facilitating smarter business operations.

- Master's or Ph.D. in Computer Science, Data Science, Machine Learning, Statistics, or related field
- Proven experience as a Data Scientist, Machine Learning Engineer, or similar role
- Extensive knowledge of deep learning frameworks such as TensorFlow, PyTorch, or Keras
- Proficiency in programming languages such as Python, R, or Java
- Strong skills in SQL and experience with databases such as MySQL, Oracle, or PostgreSQL
- Familiarity with big data tools and platforms such as Hadoop, Spark, or Kafka
- Solid understanding of machine learning algorithms and statistical methods
- Experience with data preprocessing, cleansing, and transformation techniques
- Proficiency in designing and implementing complex machine learning pipelines
- Demonstrated ability to develop, train, and tune deep learning models
- Excellent problem-solving and analytical skills with the ability to apply quantitative approaches
- Experience in deploying machine learning models in production environments
- Strong ability to write clear and comprehensive technical documentation
- Proven track record of delivering actionable insights from data to stakeholders
- Effective communication skills to explain complex technical concepts to non-technical stakeholders
- Experience in conducting code reviews and providing constructive feedback
- Familiarity with version control systems such as Git
- Strong teamwork and collaboration skills
- Continuous learner with a passion for staying updated with the latest in AI and deep learning advancements
- Experience with cloud platforms like AWS, Google Cloud, or Azure is preferred
- Ability to mentor and guide junior data scientists
- Demonstrated experience in optimizing models for performance and scalability
- Familiarity with various visualization tools and techniques for presenting data findings
- Strong project management skills with the ability to handle multiple priorities

- Analyze large sets of structured and unstructured data using advanced statistical and machine learning techniques
- Develop and implement deep learning models for various applications such as image recognition, natural language processing, and predictive analytics
- Clean, preprocess, and validate the integrity of data used for analysis
- Design and conduct experiments to test hypotheses and validate model performance
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions
- Deploy machine learning and deep learning models into production environments
- Monitor and maintain the performance of deployed models, making necessary adjustments and improvements
- Stay updated with the latest advancements in AI and deep learning technologies and apply them to ongoing projects
- Create detailed documentation for data workflows, model architectures, and experimental results
- Communicate insights and recommendations to stakeholders through reports and visualizations
- Mentor junior data scientists and provide guidance on best practices in AI and deep learning
- Participate in code reviews to ensure high-quality code and adherence to best practices in data science
- Utilize big data tools and platforms such as Hadoop, Spark, or TensorFlow for data processing and model training
- Implement scalable and efficient data pipelines for continuous data integration and model retraining
- Conduct exploratory data analysis to discover trends and patterns in data
- Optimize models for performance and scalability, considering both computational cost and accuracy
- Engage in collaborative problem-solving and knowledge sharing within the data science community of the organization

The ideal candidate for the Data Scientist (AI and Deep Learning) role is a highly analytical and detail-oriented professional with a Master's or Ph.D. in Computer Science, Data Science, Machine Learning, Statistics, or a related field, and a proven track record as a Data Scientist or Machine Learning Engineer. They possess extensive knowledge of deep learning frameworks like TensorFlow, PyTorch, or Keras, and boast proficiency in programming languages such as Python, R, or Java, along with strong skills in SQL and experience with databases like MySQL, Oracle, or PostgreSQL. This candidate has a solid grasp of machine learning algorithms, statistical methods, and experience with big data tools and platforms such as Hadoop, Spark, or Kafka. They are adept at data preprocessing, cleansing, transformation techniques, and exhibit a proven ability to develop, train, and fine-tune deep learning models. They are experienced in deploying models in production environments, maintaining and optimizing them for performance and scalability, while effectively utilizing cloud platforms like AWS, Google Cloud, or Azure. Their excellent problem-solving, analytical skills, and ability to deliver actionable insights from data set them apart. They are strong communicators, capable of explaining complex technical concepts to non-technical stakeholders, and have a knack for mentoring junior data scientists. Demonstrated experience in code review, project management, and a commitment to continuous learning and improvement further define this candidate. They thrive in fast-paced, dynamic environments, exhibit a proactive and innovative approach to problem-solving, and display strong organizational and time-management skills. Personal attributes such as a strong work ethic, high integrity, professionalism, and a passion for AI and deep learning technologies make them the ideal fit for this role.

- Analyze large sets of structured and unstructured data using advanced statistical and machine learning techniques
- Develop and implement deep learning models for various applications such as image recognition, natural language processing, and predictive analytics
- Clean, preprocess, and validate the integrity of data used for analysis
- Design and conduct experiments to test hypotheses and validate model performance
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions
- Deploy machine learning and deep learning models into production environments
- Monitor and maintain the performance of deployed models, making necessary adjustments and improvements
- Stay updated with the latest advancements in AI and deep learning technologies and apply them to ongoing projects
- Create detailed documentation for data workflows, model architectures, and experimental results
- Communicate insights and recommendations to stakeholders through reports and visualizations
- Mentor junior data scientists and provide guidance on best practices in AI and deep learning
- Participate in code reviews to ensure high-quality code and adherence to best practices in data science
- Utilize big data tools and platforms such as Hadoop, Spark, or TensorFlow for data processing and model training
- Implement scalable and efficient data pipelines for continuous data integration and model retraining
- Conduct exploratory data analysis to discover trends and patterns in data
- Optimize models for performance and scalability, considering both computational cost and accuracy
- Engage in collaborative problem-solving and knowledge sharing within the data science community of the organization

- Highly analytical and detail-oriented
- Strong passion for AI and deep learning technologies
- Proactive and self-motivated learner
- Innovative thinking and creativity in problem-solving
- Ability to thrive in a fast-paced, dynamic environment
- Excellent teamwork and collaboration skills
- Strong communication skills with technical and non-technical stakeholders
- High level of integrity and professionalism
- Strong organizational and time-management skills
- Commitment to continuous improvement and staying updated with industry trends
- Adaptability and willingness to take on new challenges
- Effective mentoring and leadership capabilities
- Enthusiasm for data-driven decision-making
- Resilience and persistence in solving complex problems
- Strong work ethic and dedication to delivering high-quality results

- Competitive salary range, commensurate with experience
- Comprehensive health, dental, and vision insurance
- Retirement savings plan with company match
- Generous paid time off and holidays
- Flexible work hours and remote work options
- Professional development and continuous learning opportunities
- Access to conferences, workshops, and industry events
- Tuition reimbursement for advanced degrees and certifications
- Employee wellness programs and resources
- Collaborative and inclusive work environment
- Access to cutting-edge AI and deep learning technology
- Opportunities for career advancement and leadership roles
- Performance-based bonuses and incentives
- Stock options or equity participation
- Paid parental leave and family support programs
- Employee assistance program (EAP) for counseling and support
- On-site gym and fitness classes or wellness stipends
- Company-sponsored social events and team-building activities
- Travel opportunities for conferences and client meetings
- Modern office space with ergonomic workstations
- Comprehensive onboarding and mentorship program
- Recognition and reward programs for outstanding performance