Clayco - Overland, MO

posted 5 months ago

Full-time - Mid Level
Overland, MO
Real Estate

About the position

Clayco is a full-service, turnkey real estate development, master planning, architecture, engineering, and construction firm that safely delivers clients across North America the highest quality solutions on time, on budget, and above and beyond expectations. With $5.8 billion in revenue for 2023, Clayco specializes in the "art and science of building," providing fast track, efficient solutions for industrial, commercial, institutional, and residential related building projects. We are currently seeking a skilled Data Scientist to join our Data Analytics team in our Overland, MO office. As a Data Scientist, you will play a critical role in understanding our business operations, identifying challenges and opportunities, and leveraging data to drive informed decision-making. You will collaborate with various stakeholders to analyze data, develop predictive models, and provide actionable insights. Additionally, you will actively contribute to the continuous improvement of our data science function and help track the business value delivered by our team. In this role, you will leverage an excellent understanding of the business operations to identify challenges and opportunities from business stakeholders and align them with available data. You will identify the relevant stage/source of data within the business process and curate and QA the necessary data using engineering skills. Performing quantitative and qualitative analysis to solve business challenges and identify actionable insights will be a key part of your responsibilities. You will also develop and validate AI/ML models, deploy them to production, and monitor their technical and business performance. Furthermore, you will apply causal inference techniques to estimate the effect of changes on relevant outcomes using experimental or non-experimental data, assess the performance of data science solutions, and define metrics to track and monitor performance and benefits to the company. Adhering to clean and reproducible programming practices, ensuring documentation for both technical and business audiences, and collaborating with project management teams to translate business requirements into detailed technical requirements will also be essential to your success in this position.

Responsibilities

  • Leverage an excellent understanding of the business operations to identify challenges and opportunities from business stakeholders and align them with available data.
  • Identify the relevant stage/source of data within the business process and curate and QA the necessary data using engineering skills.
  • Perform quantitative and qualitative analysis to solve business challenges and identify actionable insights.
  • Develop and validate AI/ML models, deploy them to production, and monitor their technical and business performance.
  • Apply causal inference techniques to estimate the effect of changes on relevant outcomes using experimental or non-experimental data.
  • Assess the performance of data science solutions and define metrics to track and monitor performance and benefits to the company.
  • Adhere to clean and reproducible programming practices, ensuring documentation for both technical and business audiences.
  • Collaborate with project management teams to translate business requirements into detailed technical requirements.
  • Create and utilize detailed test plans to evaluate data science efforts and gain alignment with business partners.

Requirements

  • Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field.
  • 3+ years of applied experience in a professional setting, with a focus on data science and analytics.
  • Strong proficiency in SQL, Python, Spark, Scala, and R programming languages.
  • Experience working with structured and non-structured data sources to build models.
  • Knowledge of AI/ML modeling techniques and ability to engineer features based on a deep understanding of the business process.
  • Familiarity with causal inference methodologies and non-parametric strategies.
  • Proficiency in platforms such as Snowflake, Tableau, DOMO, and AutoML Platforms.
  • Excellent verbal and written communication skills, with the ability to effectively communicate complex concepts to technical and non-technical stakeholders.
  • Strong documentation skills for technical and business audiences.
  • Resilience and adaptability to overcome challenges and deliver high-quality results.
  • Ability to develop and maintain detailed business knowledge to drive data-driven decision-making.

Benefits

  • 401(k)
  • Dental insurance
  • Disability insurance
  • Employee assistance program
  • Flexible spending account
  • Health insurance
  • Life insurance
  • Learning development programs
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