[Hiring] Senior Data Scientist @INSPYR Solutions

Role Description

The Senior Data Scientist plays a critical role in shaping the future of business by developing algorithms and models that forecast trends and translate business needs into actionable analytics for executive decision-making. With a strong foundation in AI/ML and pricing optimization, this role leads ML model experimentation while driving model measurement, tuning, and pilot measurement strategy. By conducting large-scale experiments, the Senior Data Scientist addresses complex business questions and uncovers hidden relationships within extensive datasets.

• Perform Exploratory Data Analysis (EDA) and initial investigations on data to discover patterns, spot anomalies, and check assumptions.
• Build predictive models using statistical and machine learning techniques, with a focus on pricing optimization and elasticity modeling.
• Augment ML model experimentation by scaling sensitivity-to-elasticity analyses, enabling more experiments and markets to run concurrently.
• Design and execute pilot measurement strategies to evaluate model performance in live environments before full deployment.
• Continuously measure, monitor, tune, and optimize models within the production environment to ensure health, accuracy, and business impact.
• Create visual representations of data to communicate findings effectively and share with other Data Scientists for input and storytelling.
• Work with cross-functional teams, including engineers, service owners, product owners, product managers, and business stakeholders, to understand data needs and challenges.
• Prepare reports and presentations to convey insights and recommendations.
• Gather data from various sources and ensure its quality and integrity.
• Stay updated with the latest tools, techniques, and industry trends in data science and AI/ML and bring ideas to the table for how to improve the use of data and analytics.
• Design and execute comprehensive data analyses using advanced methodologies and statistical modeling to produce insightful reports essential for strategic planning.
• Utilize analytical tools and hypothesis-driven analysis to enhance machine learning projects.
• Implement cutting-edge AI techniques to boost data analysis efficiency.
• Perform data sampling.

Qualifications

• Bachelor's degree in Mathematics, Statistics, Computer Science, or related field; master's degree preferred.
• Typically 5+ years of relevant quantitative and qualitative research, analytics, data science, or machine learning experience.
• Demonstrated experience with pricing optimization models and elasticity analysis.
• Experience and solid understanding of machine learning algorithms and relational databases.
• Experience with data science modeling, statistics, analytics, business intelligence, or data-driven business strategy.
• Proven experience in model measurement, monitoring, and tuning within a production environment.
• Experience managing and delivering complex and technical products.
• Experience performing statistical analysis and applying visualization techniques.
• Native-level proficiency/fluency in English.

Preferred Skills

• Knowledge of data models and structures, as well as database design tools and query languages.
• Knowledge of multiple programming languages and statistical analysis tools such as Python, C++, JavaScript, R, SAS, Excel, SQL, MATLAB, and SPSS.
• Knowledge of statistical and data mining techniques such as generalized linear models (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural networks (CNN), and recurrent neural networks (RNN).
• Strong working knowledge of AI/ML techniques with the ability to flex between data science and applied ML roles as business needs evolve.
• Experience designing and executing pilot measurement strategies and evaluating experiment results at scale across multiple markets.
• Basic knowledge of AI, its potential roles in solving business problems, and the future trajectory of generative AI models.
• Demonstrated communication, collaboration, and stakeholder management skills to build strong relationships with IT and the business.
• Demonstrated data analysis and data modeling skills to identify patterns, trends, and solutions to complex problems.
• Basic technical leadership skills encompassing employee coaching, objective setting, and fostering professional development.
• Ability to clearly communicate concepts and present complex data findings to both technical and business executives.
• Ability to conduct statistical analyses and build models with advanced scripting languages.
• Attention to detail and ability to maintain data accuracy and integrity.