Production Research Data Analyst at Bayer

Purpose: 

• The Production Research Data Analyst role is responsible for supporting the success of delivering the pipeline and data insights.
• This role will support activities related to data governance, analysis and reporting to internal and external stakeholders across Africa.
• Furthermore, responsibilities include adherence to Bayer safety, quality, and operational procedures.

Key Responsibilities: 

The Production Research Data Analyst will be responsible for:

• Building and validating dashboards using preferred visualization software
• Compiling documentation of analytical processes and results, adhering to agreed documentation standards
• Supporting process data mining from IT systems and databases
• Extract actionable insights from raw data
• Performing quality control on collected Production Research data
• Performing statistical data analyses to answer specific research questions
• Providing analytics support to various projects locally
• Providing support to stakeholders on data related deliverables using in-house analytics and reporting tools

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

• BSc or MSc in Computer Science, Data Science, Mathematics, Statistics, Biological Sciences, Computational Biology, Agriculture or similar
• 2-years’ experience in a relevant Agricultural discipline (agricultural research, plant physiology, plant breeding or related field)

Experience:

• Hands-on experience designing and building dashboards and reports using visualization tools
• Proven track record of successfully reporting data insights to stakeholders
• Strong record of problem-solving and innovation
• Experience working in a team-based environment and capacity to influence within matrixed organizations (relationships and network)
• Data mining and wrangling experience using programming languages such as R
• Proficient in downloading data from databases using software and tools such as Google Big Query

Qualifications:

Required: 

• Strong programming skills in R, Python, SQL
• Strong aptitude for statistics
• Experience with visualization software such as Tableau and TIBCO Spotfire
• Proficiency in Machine Learning and Statistics algorithms and concepts (Mixed Models, Random Forest, Deep Learning, SVM, SAS JMP etc.)
• Experience with data mining and statistical techniques (Logistic Regression, Linear Regression, Decision Trees, etc.)
• Problem solving ability and experience in analyzing and presenting complex data
• Organizational, interpersonal, and written communication skills

Desired:

• A track record of successful project delivery with analytical interpretation skills
• Willingness to be flexible and work in diverse fields and corporate conditions
• Sound decision making and judgement skills
• Detail and results oriented with the ability to work independently
• Willingness to extend personal data science and statistical interests to agriculture and/or experience working with agricultural/biological scientific data

Functional Competence:

• Ability to work in a fast-paced global and multi-cultural seed company
• Challenging the status quo to improve processes and the way things are done
• Organizational, interpersonal, and written communication skills
• Excellent data interpretation skills
• Detail and results oriented with the ability to work independently