Financial Data Scientist

Vintti is revolutionizing remote staffing by prioritizing time zone alignment. We connect US-based SMBs, startups, and firms with Latin American professionals who work synchronously with US schedules. This approach ensures that businesses can maintain their usual workflows, conduct real-time meetings, and collaborate effectively without the typical challenges of working across disparate time zones.

A Financial Data Scientist is a professional tasked with merging expertise in finance and data science to analyze complex financial datasets and extract valuable insights. This role involves utilizing advanced statistical methods, machine learning models, and data mining techniques to identify patterns, predict trends, and assist in strategic decision-making. Financial Data Scientists play a crucial role in risk management, investment analysis, and the optimization of financial operations. Their work supports organizations in understanding market behaviors, improving financial performance, and gaining a competitive edge in the industry.

- Master's degree or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Finance, or a related field.
- Minimum 3-5 years of experience in data science, machine learning, or financial analytics.
- Proficiency in programming languages such as Python, R, and SQL.
- Strong understanding of statistical methods and machine learning algorithms.
- Experience with data visualization tools like Tableau, Power BI, or similar.
- Solid knowledge of financial markets, instruments, and financial modeling.
- Proven experience in building and deploying predictive models.
- Ability to work with large, complex financial data sets and perform detailed analysis.
- Strong problem-solving skills and the ability to troubleshoot data issues.
- Excellent communication skills, both written and verbal, with the ability to convey complex concepts to non-technical stakeholders.
- Experience with data cleaning, normalization, and transformation processes.
- Familiarity with data governance policies and financial regulations.
- Demonstrated ability to collaborate effectively with cross-functional teams.
- Proven ability to work independently and manage multiple projects simultaneously.
- High attention to detail and strong organizational skills.
- Experience with cloud-based data warehousing and big data technologies (e.g., AWS, Google Cloud, Hadoop) is a plus.
- Familiarity with agile development methodologies is desirable.
- Certification in data science or financial analysis (e.g., CFA, FRM) is a plus.
- Strong mentorship and leadership skills.

- Analyze and interpret complex financial data sets using advanced statistical methods and machine learning algorithms.
- Develop predictive models to forecast financial trends and provide actionable insights for decision-making.
- Collaborate with cross-functional teams, including finance, IT, and compliance, to understand business needs and translate them into data-driven solutions.
- Design, build, and maintain data pipelines to ensure the smooth flow and integrity of financial data from various sources.
- Conduct data cleaning, normalization, and transformation processes to prepare data for analysis.
- Create and maintain detailed documentation of data analysis processes, methodologies, and findings.
- Generate and present clear, concise reports and visualizations to effectively communicate insights to both technical and non-technical stakeholders.
- Identify opportunities for process improvements and recommend system modifications to enhance data collection, analysis, and reporting.
- Stay updated on the latest developments in data science, machine learning, and financial technologies to continuously improve analytical methods.
- Participate in team meetings and contribute to strategic planning discussions by providing key data-driven inputs.
- Perform ad-hoc statistical analysis and respond to complex data queries to support financial projects and initiatives.
- Develop and test new analytical models or tools to streamline operations and improve data accuracy.
- Ensure compliance with data governance policies and financial regulations throughout all stages of data handling and analysis.
- Troubleshoot data-related issues and work on data quality initiatives to ensure high data reliability and accuracy.
- Mentor and provide guidance to junior team members on best practices in financial data science and analytical techniques.

The ideal candidate for the Financial Data Scientist role possesses a Master's degree or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Finance, or a related field, combined with 3-5 years of hands-on experience in data science, machine learning, or financial analytics. This individual demonstrates proficiency in programming languages such as Python, R, and SQL, and has a profound understanding of statistical methods and machine learning algorithms. They have a proven track record of building and deploying predictive models, working with large, complex financial data sets, and leveraging data visualization tools like Tableau or Power BI to convey actionable insights to both technical and non-technical stakeholders. An ideal candidate showcases exceptional problem-solving abilities and demonstrates meticulous attention to detail through comprehensive data cleaning, normalization, and transformation processes. Possessing strong communication skills, they effectively collaborate with cross-functional teams, including finance, IT, and compliance, to address business needs. The candidate is well-versed in financial markets, instruments, and financial modeling, and stays updated on the latest in data science and financial technologies. They exhibit strong organizational skills, are adept at managing multiple projects independently, and maintain high ethical standards in handling financial data. Additionally, experience with cloud-based data warehousing, big data technologies, and agile methodologies, along with certifications such as CFA or FRM, is highly desirable. The ideal candidate is an analytical and innovative thinker, a proactive problem solver, and a resilient professional who thrives in fast-paced and evolving environments while demonstrating empathy and patience in mentoring junior team members.

- Analyze and interpret complex financial data sets using advanced statistical methods and machine learning algorithms.
- Develop predictive models to forecast financial trends and provide actionable insights for decision-making.
- Collaborate with cross-functional teams, including finance, IT, and compliance, to understand business needs and translate them into data-driven solutions.
- Design, build, and maintain data pipelines to ensure the smooth flow and integrity of financial data from various sources.
- Conduct data cleaning, normalization, and transformation processes to prepare data for analysis.
- Create and maintain detailed documentation of data analysis processes, methodologies, and findings.
- Generate and present clear, concise reports and visualizations to effectively communicate insights to both technical and non-technical stakeholders.
- Identify opportunities for process improvements and recommend system modifications to enhance data collection, analysis, and reporting.
- Stay updated on the latest developments in data science, machine learning, and financial technologies to continuously improve analytical methods.
- Participate in team meetings and contribute to strategic planning discussions by providing key data-driven inputs.
- Perform ad-hoc statistical analysis and respond to complex data queries to support financial projects and initiatives.
- Develop and test new analytical models or tools to streamline operations and improve data accuracy.
- Ensure compliance with data governance policies and financial regulations throughout all stages of data handling and analysis.
- Troubleshoot data-related issues and work on data quality initiatives to ensure high data reliability and accuracy.
- Mentor and provide guidance to junior team members on best practices in financial data science and analytical techniques.

- Analytical mindset with a keen eye for detail
- Proactive problem solver with a strong logical approach
- Innovative thinker who is constantly looking to improve processes
- Strong collaborator and communicator across diverse teams
- Self-motivated and able to work independently
- Excellent organizational and time-management abilities
- Adaptable to fast-paced and evolving environments
- Passionate about data science and continuous learning
- Strong ethical standards and integrity in handling financial data
- Empathy and patience in mentoring junior team members
- Resilient and persistent in troubleshooting and resolving complex data issues
- Effective in translating complex data insights into actionable business strategies

- Competitive salary range: $90,000 - $140,000 per annum
- Comprehensive health, dental, and vision insurance
- Generous paid time off (PTO) and holiday schedule
- 401(k) plan with company matching
- Opportunities for professional development and certifications
- Flexible work hours and remote work options
- Employee wellness programs including gym memberships and mental health support
- Tuition reimbursement for relevant coursework and training
- Performance-based bonuses and incentives
- Company-sponsored networking and team-building events
- Access to cutting-edge technology and financial data tools
- Support for attending industry conferences and workshops
- Internal mobility options and career advancement pathways
- Parental leave and family planning support
- Life and disability insurance
- Stock options or equity participation programs