• Data engineering, including developing scripts to automate advertising analytics/survey data cleaning and process reviews using ETL/ELT pipelines with medallion architecture (Python and R) • Building and maintaining data visualizations for data exploration and trend analysis using Tableau and PowerBI dashboards. • Conduct data analysis to interpret complex data, identify patterns, and shape actionable insights (including reports, presentations, and models). This includes descriptive reporting, casual inference, segmentation, and predictive modeling. • Regular client interactions, such as presentations, reports, and status meetings to develop and refine data solutions to meet client needs, report on project progress, and share results. • Ongoing communication with vendors and internal communication campaign teams to represent findings, coordinate next steps, navigate joint decision-making, and discuss potential implications • Working in a collaborative team environment to logically design communication campaigns based on data.

• You will create cutting-edge models and solutions to enhance and streamline marketing decision-making processes, seamlessly integrating them into our market-leading technology platform. • You will assess the effectiveness of our marketing initiatives by employing advanced techniques such as attribution analysis, incrementality tests, and media mix modeling. As well as translate the resulting insights into actionable strategies that will guide our marketing budget allocation. • You will leverage your expertise in handling extensive data sets to conduct comprehensive analyses from start to finish, including data preparation, modelling training, and thorough evaluation. • You will own, improve and promote best practices and scientific models for Machine Learning, advanced statistics and predictive modeling within the team. • You will join a dynamic Data Science team and collaborate closely with a talented group of Data Engineers, Analytics Engineers and Data Analysts who bring diverse experience and skills to the table. Together, we will drive success across Emma's marketing efforts.

Role Description - Provides leadership to develop, implement and advance quantitative genetics innovations and processes in the Product Design pipeline. - Executes the quantitative genetics technical strategy to design improved cohorts of germplasm that are aligned with Product Concept targets from initial crossing through the handoff to Product Development. - Leads quantitative genetics projects on implementation of Precision Breeding technical innovations in Product Design. - Contributes strong technical and process expertise in coding, delivering, and utilizing models, algorithms and systems for: - Breeding program design and optimization - Breeding goal definition - Optimization of automated crossing processes - Genetic evaluation - Optimization of data acquisition at scale - Attracts and develops talent and serves as a mentor for peers or colleagues in key areas of expertise that support personal development. - Identifies key areas of opportunity for innovative technology implementation and/or process improvement, while positively contributing to a collaborative, innovative, and design-centric culture. - Integrates and leads multi-function teams across Product Design and partners across other world regions (LATAM, EMEA and APAC) to support innovation projects for Precision Breeding. - Focuses on driving genetic gain and product performance through digital transformation and innovative technology development and deployment. - Supports the Health Safety & Environment, Compliance, Business Conduct and Human Rights policies and culture in the site. Qualifications - Master’s degree in Quantitative Genetics, Plant Breeding, Animal Breeding, Computer science or other relevant scientific field. - Demonstrated experience working collaboratively in cross-functional and cross-cultural teams to achieve common goals. - Demonstrated experience leading and influencing activities of cross-functional teams without direct reporting relationships. - Ability to lead and influence key stakeholders through challenges, opportunities, and facilitate solutions. - Results orientation with demonstrated ability to manage multiple projects/priorities simultaneously. - Experienced in building and operating processes for the analysis of large biological data sets, quantitative genetics, statistical genetics, as well as coding experience in C, Fortran, R or similar languages. - Strong collaboration and ability demonstrated through building cross-functional partnerships and influencing others to drive results and innovation focused on solving business problems. - Demonstrated ability to manage complex problems. Requirements - Demonstrated track record of success and 6+ years of experience in deriving quantitative genetics theory, in coding, in delivering and in utilizing models, algorithms and systems for at least three of the following areas: - Breeding program design and optimization - Breeding goal definition - Optimization of automated crossing processes - Genetic evaluation - Optimization of data acquisition at scale in plant or animal breeding programs - Execution of quantitative genetics processes at scale in plant or animal breeding programs - Ph.D. degree in Quantitative Genetics, Plant Breeding, Animal Breeding, or other relevant scientific field. - 6-10+ years of experience in developing quantitative genetics methods and processes for routine use in breeding programs. Benefits - Salary range: $120,560.00 to $180,840.00. - Additional compensation may include a bonus or commission (if relevant). - Additional benefits include health care, vision, dental, retirement, PTO, sick leave, etc.

• Maintain data pipelines for automated data processing suitable for downstream reporting, tabling, and summarizing • Execute and build upon reproducible reports via efficient code for complex tabling and data visualization. • Contribute to internal or external R packages. • Collaborate with Clinical Operations and Data Management teams to understand emerging trial and business needs, assess available data, and determine how to appropriately summarize and present results.