All associates are guided by Our Values. Our Values are the unifying foundation of our companies. We strive to ensure that every decision we make and every action we take demonstrates Our Values. We believe that putting Our Values into practice creates lasting benefits for all our associates, shareholders, and the communities in which we live.
JOB SUMMARY
The Data Scientist - Machine Learning at The Friedkin Group (TFG) will design, develop, implement, maintain, and improve advanced data science initiatives across business units, directly aligning with strategic objectives. This role encompasses transforming innovative ideas into real-world solutions through the application of sophisticated analytical techniques such as machine learning, optimization, and advanced analysis.
The incumbent will deliver impactful analytical solutions, ensuring these innovations are seamlessly embedded into business operations to drive decision-making, enhance operational efficiency, and foster a culture of continuous improvement and innovation. As part of this role the applicant will play a significant part in setting the AI & ML agenda for The Friedkin Group, including working with business units to define potential opportunities, and defining standards and best practice for AI & ML at TFG.
ESSENTIAL FUNCTIONS
Design, train, and implement machine learning (supervised and unsupervised) algorithms
Build, deploy, and maintain machine learning algorithms, interface endpoints, and back-end data infrastructure for digital products.
Perform data mining, exploration, and time series analysis
Designs machine learning and advanced analytics solutions, algorithms, and cloud architectures needed to satisfy product features and functionality defined by product owner and other stakeholders in a production environment
Works in all phases of the software development life cycle including functional analysis, development of technical requirements, technical design, prototyping, coding, testing, deployment, data migration, and support
Assists in integrating subsystems such as data pipelines, AI/ML algorithms, API interfaces into end-user facing products
Participate in daily scrums, work with Scrum Master and QA Team on projects, and support delivery timelines and priorities
Organizes and prioritizes individual workload with scrum team through story pointing
Creates detailed documentation which describes methodology, relevant instructions, and test results
Finds, analyzes, and fixes bugs and performance problems whenever and wherever they may occur
SUPERVISORY RESPONSIBILITIES
May supervise or oversee the work of one or more employees or contractors. Carries out responsibilities in accordance with the organization's policies and applicable laws.
Demonstrated ability to lead and manage data science projects, including, managing workflow and priorities, to ensure timely delivery of projects with high-quality outcomes.
Proven track record of recruiting, training, and retaining a skilled data science team, identifying talent gaps, and addressing them.
QUALIFICATIONS
Bachelor’s degree in a related discipline and 4 years’ experience in a related field. The right candidate could also have a different combination, such as a master’s degree and 2 years’ experience; a Ph.D. and up to 1 year of experience; or 8 years’ experience in a related field
Proficient in at least one analytical programming language relevant for data science. Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI).
Experience with Time-Series Forecasting Methods, Regression Models, Clustering/Dimensionality Reduction
Familiarity with Mixed-Integer-Linear-Programming Algorithms, CPLEX, Gurobi
Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark).
Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop.
Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, pattern recognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms.,
Good understanding of programming best practices, building for re-use and highly automated CI/CD pipelines.
SOFT SKILLS
Proven track record of leading cross-functional teams to successfully deliver complex data-driven projects.
Excellent problem-solving and analytical skills, with the ability to translate complex technical details into understandable business insights.
Sees overall 'picture' and alternative approaches and develop vision of what may be possible.
Strong interpersonal and communication skills, capable of working effectively with and developing trust from both non-technical and technical counterparts to influence key use case & enterprise decisions.
CERTIFICATES, LICENSES, REGISTRATIONS*
Relevant certifications such as Microsoft Certified: Azure Data Scientist Associate or AWS Certified Machine Learning are advantageous.
PHYSICAL REQUIREMENTS
The physical requirements described here are representative of those that must be met by an associate to successfully perform the essential functions of the job. While performing the duties of the job, the associate is required daily to analyze and interpret data, communicate, and remain in a stationary position for a significant amount of the workday; and frequently access, input, and retrieve information from the computer and other office productivity devices. The associate is regularly required to move about the office and around the corporate campus. The associate is occasionally required to travel to other sites, including out-of-state, where applicable, for business. The associate must frequently move up to 10 pounds and occasionally move up to 25 pounds.
WORK ENVIRONMENT
The work environment characteristics described here are representative of those associate encounters while performing the essential functions of this job. While the job is generally performed in an office environment, the associate is occasionally exposed to wet and/or humid conditions, areas in which moving mechanical parts, fumes, toxic or caustic chemicals are present, and outside weather conditions. The noise level in the office environment is typically quiet, but the associate may be occasionally exposed to loud noise levels.
TRAVEL REQUIRED
Minimal travel is required for this position (up to 20% of the time and on a domestic basis).
The Friedkin Group and its affiliates are equal opportunity employers and maintain drug-free workplaces by conducting pre-employment drug testing.
LIVING OUR VALUES
All associates are guided by Our Values. Our Values are the unifying foundation of our companies. We strive to ensure that every decision we make and every action we take demonstrates Our Values. We believe that putting Our Values into practice creates lasting benefits for all our associates, shareholders, and the communities in which we live.
JOB SUMMARY
The Data Scientist - Machine Learning at The Friedkin Group (TFG) will design, develop, implement, maintain, and improve advanced data science initiatives across business units, directly aligning with strategic objectives. This role encompasses transforming innovative ideas into real-world solutions through the application of sophisticated analytical techniques such as machine learning, optimization, and advanced analysis.
The incumbent will deliver impactful analytical solutions, ensuring these innovations are seamlessly embedded into business operations to drive decision-making, enhance operational efficiency, and foster a culture of continuous improvement and innovation. As part of this role the applicant will play a significant part in setting the AI & ML agenda for The Friedkin Group, including working with business units to define potential opportunities, and defining standards and best practice for AI & ML at TFG.
ESSENTIAL FUNCTIONS
Design, train, and implement machine learning (supervised and unsupervised) algorithms
Build, deploy, and maintain machine learning algorithms, interface endpoints, and back-end data infrastructure for digital products.
Perform data mining, exploration, and time series analysis
Designs machine learning and advanced analytics solutions, algorithms, and cloud architectures needed to satisfy product features and functionality defined by product owner and other stakeholders in a production environment
Works in all phases of the software development life cycle including functional analysis, development of technical requirements, technical design, prototyping, coding, testing, deployment, data migration, and support
Assists in integrating subsystems such as data pipelines, AI/ML algorithms, API interfaces into end-user facing products
Participate in daily scrums, work with Scrum Master and QA Team on projects, and support delivery timelines and priorities
Organizes and prioritizes individual workload with scrum team through story pointing
Creates detailed documentation which describes methodology, relevant instructions, and test results
Finds, analyzes, and fixes bugs and performance problems whenever and wherever they may occur
SUPERVISORY RESPONSIBILITIES
May supervise or oversee the work of one or more employees or contractors. Carries out responsibilities in accordance with the organization's policies and applicable laws.
Demonstrated ability to lead and manage data science projects, including, managing workflow and priorities, to ensure timely delivery of projects with high-quality outcomes.
Proven track record of recruiting, training, and retaining a skilled data science team, identifying talent gaps, and addressing them.
QUALIFICATIONS
Bachelor’s degree in a related discipline and 4 years’ experience in a related field. The right candidate could also have a different combination, such as a master’s degree and 2 years’ experience; a Ph.D. and up to 1 year of experience; or 8 years’ experience in a related field
Proficient in at least one analytical programming language relevant for data science. Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI).
Experience with Time-Series Forecasting Methods, Regression Models, Clustering/Dimensionality Reduction
Familiarity with Mixed-Integer-Linear-Programming Algorithms, CPLEX, Gurobi
Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark).
Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop.
Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, pattern recognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms.,
Good understanding of programming best practices, building for re-use and highly automated CI/CD pipelines.
SOFT SKILLS
Proven track record of leading cross-functional teams to successfully deliver complex data-driven projects.
Excellent problem-solving and analytical skills, with the ability to translate complex technical details into understandable business insights.
Sees overall 'picture' and alternative approaches and develop vision of what may be possible.
Strong interpersonal and communication skills, capable of working effectively with and developing trust from both non-technical and technical counterparts to influence key use case & enterprise decisions.
CERTIFICATES, LICENSES, REGISTRATIONS*
Relevant certifications such as Microsoft Certified: Azure Data Scientist Associate or AWS Certified Machine Learning are advantageous.
PHYSICAL REQUIREMENTS
The physical requirements described here are representative of those that must be met by an associate to successfully perform the essential functions of the job. While performing the duties of the job, the associate is required daily to analyze and interpret data, communicate, and remain in a stationary position for a significant amount of the workday; and frequently access, input, and retrieve information from the computer and other office productivity devices. The associate is regularly required to move about the office and around the corporate campus. The associate is occasionally required to travel to other sites, including out-of-state, where applicable, for business. The associate must frequently move up to 10 pounds and occasionally move up to 25 pounds.
WORK ENVIRONMENT
The work environment characteristics described here are representative of those associate encounters while performing the essential functions of this job. While the job is generally performed in an office environment, the associate is occasionally exposed to wet and/or humid conditions, areas in which moving mechanical parts, fumes, toxic or caustic chemicals are present, and outside weather conditions. The noise level in the office environment is typically quiet, but the associate may be occasionally exposed to loud noise levels.
TRAVEL REQUIRED
Minimal travel is required for this position (up to 20% of the time and on a domestic basis).
The Friedkin Group and its affiliates are equal opportunity employers and maintain drug-free workplaces by conducting pre-employment drug testing.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Executive Offices
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