Luma Financial Technologies, LLC
Data Scientist
Luma Financial Technologies, LLC, Cincinnati, Ohio, United States, 45208
Join to apply for the
Data Scientist
role at
Luma Financial Technologies .
A Data Scientist in the financial investment sector focused on analytics, with a range of responsibilities that combine technical expertise, domain knowledge, and leadership.
What you'll do
Leadership and Mentorship
Team Leadership : Lead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development.
Project Management : Oversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results.
Innovation and Continuous Learning:
Stay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team.
Collaboration with Cross-Functional Teams
Stakeholder Engagement:
Work closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions.
Communication of Insights:
Present complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions.
Advanced Data Analysis and Modeling
Develop Predictive Models:
Create and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting.
Quantitative Research:
Conduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets.
Statistical Analysis:
Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk.
Business Impact and ROI
Performance Metrics:
Define and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance.
Cost-Benefit Analysis:
Perform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI).
Algorithmic Trading and Automation
Algorithm Development:
Develop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques.
Back testing and Simulation:
Conduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions.
What we're looking for
Advanced Statistical Techniques:
Expertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics.
Machine Learning and AI:
Proficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP).
Programming Languages:
Strong coding skills in languages like Python, commonly used for data analysis, modeling, and automation.
Data Management:
Experience with big data technologies, and relational databases to handle and manipulate large datasets.
Data Visualization:
Proficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders.
Cloud Computing:
Familiarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions.
Quantitative Analysis:
Deep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics.
Algorithmic Trading:
Experience in developing and back testing trading algorithms using quantitative models and data-driven strategies.
Requirements:
A bachelor's degree in a related field, such as computer science, data science, or statistics.
Proven experience (5-7 years) in programming languages, machine learning, data visualization and statistical analysis.
Founded in 2018, Luma Financial Technologies (“Luma”) has pioneered a cutting-edge fintech software platform that has been adopted by broker/dealer firms, RIA offices, and private banks around the world. By using Luma, institutional and retail investors have a fully customizable, independent, buy-side technology platform that helps financial teams more efficiently learn about, research, purchase, and manage alternative investments as well as annuities. Luma gives these users the ability to oversee the full, end-to-end process lifecycle by offering a suite of solutions. These include education resources and training materials; creation and pricing of custom structured products; electronic order entry; and post-trade management. By prioritizing transparency and ease of use, Luma is a multi-issuer, multi-wholesaler, and multi-product option that advisors can utilize to best meet their clients’ specific portfolio needs. Headquartered in Cincinnati, OH, Luma also has offices in New York, NY, Zurich, Switzerland, and Miami, FL. For more information, please visit Luma’s website.
Seniority level:
Mid-Senior level
Employment type:
Full-time
Job function:
Engineering and Information Technology
Get notified about new Data Scientist jobs in
Cincinnati, OH .
Cincinnati, OH $130,000.00-$150,000.00
#J-18808-Ljbffr
Data Scientist
role at
Luma Financial Technologies .
A Data Scientist in the financial investment sector focused on analytics, with a range of responsibilities that combine technical expertise, domain knowledge, and leadership.
What you'll do
Leadership and Mentorship
Team Leadership : Lead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development.
Project Management : Oversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results.
Innovation and Continuous Learning:
Stay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team.
Collaboration with Cross-Functional Teams
Stakeholder Engagement:
Work closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions.
Communication of Insights:
Present complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions.
Advanced Data Analysis and Modeling
Develop Predictive Models:
Create and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting.
Quantitative Research:
Conduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets.
Statistical Analysis:
Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk.
Business Impact and ROI
Performance Metrics:
Define and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance.
Cost-Benefit Analysis:
Perform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI).
Algorithmic Trading and Automation
Algorithm Development:
Develop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques.
Back testing and Simulation:
Conduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions.
What we're looking for
Advanced Statistical Techniques:
Expertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics.
Machine Learning and AI:
Proficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP).
Programming Languages:
Strong coding skills in languages like Python, commonly used for data analysis, modeling, and automation.
Data Management:
Experience with big data technologies, and relational databases to handle and manipulate large datasets.
Data Visualization:
Proficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders.
Cloud Computing:
Familiarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions.
Quantitative Analysis:
Deep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics.
Algorithmic Trading:
Experience in developing and back testing trading algorithms using quantitative models and data-driven strategies.
Requirements:
A bachelor's degree in a related field, such as computer science, data science, or statistics.
Proven experience (5-7 years) in programming languages, machine learning, data visualization and statistical analysis.
Founded in 2018, Luma Financial Technologies (“Luma”) has pioneered a cutting-edge fintech software platform that has been adopted by broker/dealer firms, RIA offices, and private banks around the world. By using Luma, institutional and retail investors have a fully customizable, independent, buy-side technology platform that helps financial teams more efficiently learn about, research, purchase, and manage alternative investments as well as annuities. Luma gives these users the ability to oversee the full, end-to-end process lifecycle by offering a suite of solutions. These include education resources and training materials; creation and pricing of custom structured products; electronic order entry; and post-trade management. By prioritizing transparency and ease of use, Luma is a multi-issuer, multi-wholesaler, and multi-product option that advisors can utilize to best meet their clients’ specific portfolio needs. Headquartered in Cincinnati, OH, Luma also has offices in New York, NY, Zurich, Switzerland, and Miami, FL. For more information, please visit Luma’s website.
Seniority level:
Mid-Senior level
Employment type:
Full-time
Job function:
Engineering and Information Technology
Get notified about new Data Scientist jobs in
Cincinnati, OH .
Cincinnati, OH $130,000.00-$150,000.00
#J-18808-Ljbffr