Data Mining Engineer

Vintti bridges the staffing gap for US businesses with a unique focus on time zone compatibility. We source top talent from Latin America, offering companies access to professionals who are available during standard US working hours. This alignment eliminates the need for off-hour communications and allows for integrated teamwork, as if all team members were in the same office.

A Data Mining Engineer plays a pivotal role in transforming raw data into actionable insights through the use of complex algorithms and statistical models. This role involves extracting and processing large volumes of structured and unstructured data to uncover patterns, trends, and correlations that drive strategic decisions. Data Mining Engineers work collaboratively with cross-functional teams to identify business needs, clean and organize data, and implement machine learning techniques to create predictive models. Their expertise in handling big data and their keen analytical skills are essential for optimizing processes, enhancing customer experiences, and driving innovation within an organization.

- Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field
- Proven experience as a Data Mining Engineer or in a similar role
- Strong proficiency in programming languages such as Python, R, or Java
- Experience with data mining frameworks and tools (e.g., WEKA, RapidMiner)
- Expertise in SQL and database management systems
- Familiarity with machine learning libraries and tools (e.g., TensorFlow, scikit-learn)
- Solid understanding of statistical analysis and data modeling techniques
- Experience with big data technologies (e.g., Hadoop, Spark)
- Familiarity with ETL (Extract, Transform, Load) processes and tools
- Strong analytical and problem-solving skills
- Experience with data visualization tools (e.g., Tableau, Power BI)
- Excellent communication and presentation skills
- Ability to work collaboratively in a team environment
- Attention to detail and commitment to quality
- Ability to manage multiple projects and priorities effectively
- Knowledge of cloud computing platforms (e.g., AWS, Google Cloud, Azure) is a plus
- Familiarity with version control systems such as Git
- Understanding of data governance and data privacy standards
- Strong organizational and documentation skills
- Continuous learning mindset with a keen interest in staying updated with evolving data technologies and methodologies.

- Extract and analyze large datasets to identify patterns and trends.
- Develop and deploy data mining algorithms and predictive models.
- Collaborate with cross-functional teams to define data requirements.
- Perform exploratory data analysis to uncover hidden insights.
- Integrate new data sources to enhance data mining capabilities.
- Optimize data extraction and transformation processes.
- Apply machine learning techniques for forecasting and classification.
- Maintain and update data mining tools and software.
- Conduct testing and validation of data models for accuracy.
- Prepare and present data reports and visualizations.
- Monitor and troubleshoot data quality and pipeline performance.
- Stay updated with advancements in data mining and machine learning.
- Document processes, models, and findings for team knowledge sharing.

The ideal candidate for the role of Data Mining Engineer will possess a Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field, coupled with proven experience in a similar capacity. They will demonstrate strong proficiency in programming languages such as Python, R, or Java, and have hands-on experience with data mining frameworks and tools like WEKA or RapidMiner. This individual will showcase expertise in SQL and database management systems, alongside familiarity with machine learning libraries and tools such as TensorFlow and scikit-learn. Their solid understanding of statistical analysis, data modeling techniques, and experience with big data technologies like Hadoop and Spark, will be crucial. They will excel in ETL processes, ensuring data quality and optimizing data extraction and transformation processes. The ideal candidate will possess excellent analytical and problem-solving skills, with a keen attention to detail and a high commitment to quality. They will be adept at using data visualization tools like Tableau or Power BI, and have excellent communication and presentation skills for both technical and non-technical audiences. They will thrive in collaborative environments, be proactive and self-motivated with a continuous learning mindset, and possess strong organizational and documentation skills. Experience with cloud computing platforms such as AWS, Google Cloud, or Azure, and familiarity with version control systems like Git will be advantageous. Ultimately, they will be a dependable and accountable professional, capable of managing multiple projects and deadlines efficiently, and committed to staying updated with evolving data technologies and methodologies.

- Extract, clean, and analyze large datasets from various sources to identify patterns and actionable insights.
- Develop and implement data mining algorithms and predictive models to improve business processes and decision-making.
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver relevant solutions.
- Perform exploratory data analysis to uncover hidden trends and relationships within datasets.
- Integrate and manage new data sources to expand the capabilities and scope of data mining operations.
- Optimize data extraction and transformation processes to ensure efficiency and scalability.
- Apply machine learning techniques to build and refine models for forecasting and classification tasks.
- Maintain and update data mining tools and software to leverage the latest technologies and methodologies.
- Conduct rigorous testing and validation of data models to ensure accuracy and reliability.
- Prepare and present detailed reports and visualizations of data findings to technical and non-technical audiences.
- Monitor and troubleshoot issues related to data quality and data pipeline performance.
- Stay current with advancements in data mining, machine learning, and related technologies to continuously improve methodologies.
- Document processes, models, and findings to ensure reproducibility and knowledge sharing across the team.

- Strong analytical and problem-solving skills
- Keen attention to detail and high commitment to quality
- Ability to think critically and uncover insights from complex datasets
- Strong proficiency in programming and statistical languages
- Excellent communication and presentation skills for both technical and non-technical audiences
- Collaborative mindset with the ability to work effectively in team settings
- Proactive and self-motivated with an aptitude for continuous learning
- Ability to manage multiple projects and deadlines efficiently
- Strong organizational and documentation skills
- Adaptability to rapidly evolving technologies and methodologies
- Dependability and accountability in delivering accurate and reliable results
- Innovative thinking to develop and implement data-driven solutions

- Competitive salary range of $90,000 - $120,000 annually
- Comprehensive health, dental, and vision insurance plans
- Generous paid time off (PTO) and holiday leave
- Flexible work hours and remote work options
- 401(k) retirement plan with company matching
- Professional development and continuous learning opportunities
- Tuition reimbursement for relevant courses and certifications
- Access to cutting-edge technology and tools
- Employee wellness programs and gym membership discounts
- Parental leave and family support programs
- Regular team-building activities and company events
- Opportunities for career advancement and promotion
- Employee stock purchase plan (ESPP)
- Free snacks, beverages, and catered lunches
- Commuter benefits and on-site parking