Africa Production Research Data Scientist

Purpose:

• The Production Research Data Scientist will be responsible for data management systems and data analytics activities within the Africa and EMEA-A region.
• Accountabilities include managing team databases, developing data management systems, securing data quality and integrity, data analysis and developing visualization and modeling tools.
• Leads specific projects within the region and is part of a global data analytics network to support broad initiatives and represent Africa in the Global Data Analytics network to help shape global PR strategy, governance, and projects.

Scope (regional, local, global):

• Support Row Crop Data Science focusing on descriptive, diagnostic and prescriptive analysis.
• Data availability (data gathering, data quality, data access and database management system).
• Implementing data projects supporting Global and Regional strategy in partnership with SPR Regional Leadership Team.

Key Responsibilities:

• Provide data management technical expertise & support, as needed, in solving critical business issues.
• Responsible for consolidation, summarization, and analysis of Parent Test data to drive critical processes such as:
  
  • Regional Portfolio Management Process
  • Foundation Seed Production Planting Instructions
  • Hybrid Seed Production Planting Instructions
  • Hybrid Seed Production Yield Forecasting across Africa
• Data source mapping, data gathering, data access to support Data Base building process.
• Independently develop algorithms in R and/or Python for data quality processes, analyze and visualize large multivariate datasets
• Perform specific projects (descriptive analysis, BI analysis and visualization), establishing a strong connection with regional & global teams.
• Attend regional and global missions to support projects identification and results presentation.
• Decision Analytics: Understands and articulates the advantages and limitations of project data and statistical models used in seed production.
• Innovation: Actively learns and applies new tools e.g. SQL, Tableau, Spotfire. Power BI-Collaborates with subject matter experts, business stakeholders, and other analysts.
• Consolidate, Monitor and Communicate to leadership statistical indicators to support data compliance and reliability.
• Support KPIs build up and follow up with action plans to team members.
• Support regional team with statistical data analysis.
• Support Production Research team with building data visualization and training on the use of data visualization tools.
• Manage Row Crop Production Research / Parent Test databases.
• Develop data management systems to ensure proper data QC processes and data integrity.
• Work closely with RSA and SSA Research and Testing Mission Coordinators to drive sound data management.
• Provide guidelines for database audit process and compliance.
• Actively participate on cross-regional teams and initiatives to leverage global data and knowledge, build consistent data processes, and leverage global information.
• Must be able to travel and support the needs within the Africa region.
• Manage the Africa Production Support QMS system (ISO9001).
• HSE Responsibilities:
  
  • Leading HSE efforts according to ISO 45001 and Bayer safety standards focusing on legal compliance and identifying safety risks applying the HIRA methodology.
  • Adherence to all applicable legislation, Bayer safety policies and procedures.
  • Actively promoting the Bayer safety culture and best practices.
  • Participation in compiling Risk assessments and Job safety analysis.
  • Actively recording safety observation and near misses.
  • Participating in 5WHY problem solving identifying corrective and preventative actions.

Key Working Relations:

• Data Insights and Pipeline Advancement Unit
• SSA and RSA Research and Testing Missions
• Agronomy and Technology Deploy Mission
• Foundation and Commercial Seed Production
• Production Management
• Production Quality
• Breeding (R&D)
• Portfolio Management

Qualifications & Experience:

Education:

• MSc. in Data Sciences or related Agricultural discipline with 5+ years’ experience Agronomy/Plant Science; or BSc/MSc in Agronomy/Plant Science with strong data analytics aptitude.

Experience:

• Excellent project management and organizational skills.
• Excellent communication – oral, written, under diverse circumstances and audiences.
• Strong technical aptitude on data management, data analysis, data mining, data visualization tools, predictive analytics, and modeling.
• A track record of successful project delivery.
• Decision making and problem-solving skills.
• Act in solving problems while exhibiting judgment and a realistic understanding of issues.

Qualifications:

Required:

• Proven data science experience in the life sciences field.
• Strong statistical skills.
• Extensive experience processing, analyzing, and visualizing large datasets.
• Excellent oral and written communications skills.

Desired:

• Additional experience in Predictive Analytics, Modelling, and Simulation.
• Sound decision making and judgement skills.
• Six Sigma or Lean manufacturing expertise.

Functional Competencies:

• Excellent human relation skills, effective oral and written communication skills required. Capability to clearly present information and influence or persuade others (multilingual in local language / English).
• The ability to communicate with different reporting levels in multi-national and cultural organizations as an individual or a team.
• Ability to work in a fast-paced global and multi-cultural seed company.
• Decision making and problem-solving skills.
• Act in solving problems while exhibiting judgment and a realistic understanding of issues.
• Challenging the status quo to improve processes and the way things are done.

Bayer welcomes applications from all individuals, regardless of race, national origin, gender, age, physical characteristics, social origin, disability, union membership, religion, family status, pregnancy, sexual orientation, gender identity, gender expression or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination.