Precision Genomics Data Science Co-op
for each section. Use - for lists. Use
for prose.
We must not repeat job title. No Job ID etc. Remove boilerplate: cookie/navigation/legal/EEO etc. Also remove application instructions like "YOUR APPLICATION ..." and "To all recruitment agencies..." etc. Also remove location line? It's metadata; we can fold minor metadata into short
or drop it. Probably drop location line.
We need preserve all substantive information: role description, tasks, responsibilities, key working relationships, who you are (required qualifications, preferred qualifications), salary range, benefits.
We need to structure sections: About the role (intro paragraph), Responsibilities (list), Key Working Relationships maybe part of Responsibilities? Could be separate but we can include under Responsibilities or as its own section. The instruction: use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should follow those headings exactly if content exists. So we need sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay. Possibly Skills separate from Requirements? The posting has Required Qualifications and Preferred Qualifications. Could map Requirements to required qualifications, Qualifications to preferred? Or Skills separate. But we have to decide.
We have: Required Qualifications (list), Preferred Qualifications (list). Also there is mention of skills: "Intermediate proficiency in computational skills... Strong proficiency in predictive modeling... Intermediate proficiency in machine learning algorithms... Experience delivering valuable analysis... Strong communication skills". Those could go under Skills.
Thus we can have:
- About the role: intro paragraph describing role.
- Responsibilities: list of tasks and responsibilities (the bullet list under "Your Tasks And Responsibilities").
- Requirements: maybe required qualifications.
- Qualifications: maybe preferred qualifications.
- Skills: list of skills (computational proficiency, predictive modeling, machine learning, business acumen, communication).
- Benefits: list of benefits.
- Pay: salary range.
We must not include Schedule.
We must not include filler like "commensurate with experience". Not present.
We must preserve all substantive information. Ensure we include key working relationships? That is part of responsibilities maybe. Could embed in Responsibilities list as an item. The posting includes "Key Working Relationships:" paragraph. We should include that as part of Responsibilities or maybe as its own section but not in allowed headings. Since only allowed headings are those, we should incorporate into Responsibilities.
Thus Responsibilities list items:
- Maximize the use of large‑scale genomics and metadata to support high‑throughput DNA genotyping and sequencing production and workflow development needs;
- Independently perform bioinformatic analysis, computer programming, and experimental design;
- Use and maintain advanced bioinformatic pipelines and databases for mining and visualizing large genomic data sets to deliver insights, recommendations, and solutions;
- Provide technical contributions in a fast‑paced team environment to accelerate efforts on building an analytics‑driven product pipeline;
- Develop sustainable, consumable, accurate, and impactful reporting on analysis inputs, analysis outputs, biological interpretation, business impact, and key performance indicators;
- Present compelling, validated stories to all levels of the organization, including peers, senior management, and internal customers, to drive both strategic and operational changes in the business;
- Demonstrate a moderate level of autonomy in developing relationships for effective cross‑functional collaboration across multiple organizations and partners on work stream initiatives for the Data Science community.
- Active member of the Data Science community to build personal acumen and ability while sharing best practices with others;
- Builds relationships and networks within the current function, with guidance as needed to expand networks cross‑functionally;
- Interacts most often with Bioinformaticians and Data Scientists within the organization and peer business partners;
- Reports to a Precision Genomics Analytics & Insights Lead but independently drives data science projects with key stakeholders spanning functions and countries.
We need to keep the semicolons? Probably just plain text.
Now Required Qualifications list:
- Currently pursuing a Master’s or Ph.D. in a relevant discipline (Data Science, Machine Learning, Electrical/Industrial Engineering, Statistical Genetics, Statistics, Biostatistics, Bioinformatics, Genomics, Computational Biology, Applied Mathematics, Computer Science, or other related quantitative discipline);
- Intermediate proficiency in computational skills and experience building data models using R, Python, or other statistical and/or mathematical programming packages;
- Strong proficiency in predictive modeling, including comprehension of theory, modeling/identification strategies, and awareness of limitations and pitfalls;
- Intermediate proficiency in machine learning algorithms and concepts;
- Experience delivering valuable analysis through application of domain knowledge, demonstrating strong business acumen;
- Strong communication skills, including the ability to present and deliver complex quantitative analyses in a clear, concise, and actionable manner to extended teams and small groups of key stakeholders.
Preferred Qualifications list:
- One to two years of experience with machine learning modeling and working with genomics data;
- Strong analytical and problem‑solving skills.
Skills section: maybe we can combine some of the above but we already have them in qualifications. However we need a Skills section per instruction; we could list skills like: computational skills (R, Python), predictive modeling, machine learning, business acumen, communication. But that duplicates qualifications. Might be okay but we risk duplication. Perhaps we treat Required Qualifications as Requirements, Preferred Qualifications as Qualifications, and Skills as a summary of key skills extracted (like computational skills, predictive modeling, machine learning, business acumen, communication). But that would lose some detail? The instruction says preserve ALL substantive information; we can't omit details. If we put skills as a separate section, we need to include all skill-related info somewhere. Could put them in Skills section and not duplicate elsewhere. Then Requirements and Qualifications could focus on education/experience. Let's parse:
Required Qualifications includes education and proficiency statements. Those are both qualifications and skills. But we can split: Requirements: education (currently pursuing Master's/PhD). Qualifications: experience (maybe none). But the posting also has "Preferred Qualifications". Hmm.
Better to follow the headings exactly: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay.
We need to map content:
- About the role: intro paragraph.
- Responsibilities: list of tasks and responsibilities (including key working relationships).
- Requirements: Required Qualifications (the list).
- Qualifications: Preferred Qualifications (the list).
- Skills: maybe we can list the specific skill proficiencies mentioned: computational skills (R, Python), predictive modeling, machine learning algorithms, business acumen, communication skills. But those are already in Required Qualifications. However we can still list them; duplication may be okay but risk of repeating info. The instruction says preserve ALL substantive information; repeating is not prohibited but could be considered redundant. However it's safer to not duplicate; we can put skill details under Skills and not repeat them in Requirements/Qualifications. Then Requirements would be just education? But Required Qualifications includes education plus skill proficiencies. If we move skill proficiencies to Skills, we lose them from Requirements unless we also keep them there. But we could keep education in Requirements and move skill proficiencies to Skills. Then Qualifications (Preferred) stays as is.
Thus:
Requirements (education): Currently pursuing a Master’s or Ph.D. in a relevant discipline (list).
Skills: Intermediate proficiency in computational skills and experience building data models using R, Python, or other statistical and/or mathematical programming packages; Strong proficiency in predictive modeling, including comprehension of theory, modeling/identification strategies, and awareness of limitations and pitfalls; Intermediate proficiency in machine learning algorithms and concepts; Experience delivering valuable analysis through application of domain knowledge, demonstrating strong business acumen; Strong communication skills, including the ability to present and deliver complex quantitative analyses in a clear, concise, and actionable manner to extended teams and small groups of key stakeholders.
Qualifications (Preferred): One to two years of experience with machine learning modeling and working with genomics data; Strong analytical and problem‑solving skills.
That covers all substantive info.
Now Benefits: list: health care, vision, dental, retirement, PTO, sick leave, etc (if relevant). Also mention bonus or commission (if relevant). Actually bonus/compensation mentioned under Pay? The posting says: "Employees can expect to be paid a salary of approximately between $22.75 to $47.75. Additional compensation may include a bonus or commission (if relevant). Additional benefits may include health care, vision, dental, retirement, PTO, sick leave, etc (if relevant)." So Pay section: salary range and note about bonus/commission. Benefits section: list of benefits.
We must not include filler like "if relevant". It's part of the posting; we keep it.
Now About the role: combine first two paragraphs: "In this role within the Precision Genomics group, you will work collaboratively with interdisciplinary scientists, IT, and engineering professionals to optimize DNA genotyping and sequencing workflows and answer key questions that drive decisions for Precision Genomics and partners across Breeding, Biotech, and Product Supply. As an individual contributor on the Precision Genomics Analytics team, you will help build an analytics‑driven product pipeline by applying advanced mathematical models, machine learning algorithms, and operations research techniques, combined with strong business acumen, to deliver insights, recommendations, and solutions."
That's it.
Now produce HTML fragment:
About the role
...
Responsibilities
- ...
...
Requirements
- Currently pursuing a Master’s or Ph.D. in a relevant discipline (Data Science, Machine Learning, Electrical/Industrial Engineering, Statistical Genetics, Statistics, Biostatistics, Bioinformatics, Genomics, Computational Biology, Applied Mathematics, Computer Science, or other related quantitative discipline);
Skills
- Intermediate proficiency in computational skills and experience building data models using R, Python, or other statistical and/or mathematical programming packages;
- Strong proficiency in predictive modeling, including comprehension of theory, modeling/identification strategies, and awareness of limitations and pitfalls;
- Intermediate proficiency in machine learning algorithms and concepts;
- Experience delivering valuable analysis through application of domain knowledge, demonstrating strong business acumen;
- Strong communication skills, including the ability to present and deliver complex quantitative analyses in a clear, concise, and actionable manner to extended teams and small groups of key stakeholders;
Qualifications
- One to two years of experience with machine learning modeling and working with genomics data;
- Strong analytical and problem‑solving skills.
Benefits
- health care
- vision
- dental
- retirement
- PTO
- sick leave
- etc (if relevant)
Pay
Employees can expect to be paid a salary of approximately between $22.75 to $47.75. Additional compensation may include a bonus or commission (if relevant).
We need to ensure we didn't include Schedule. Good.
Check for any boilerplate removed: we removed location line, reference code, contact info, EEO statements, application instructions, etc.
We kept all substantive info: role description, responsibilities, key working relationships, required qualifications (education), skills, preferred qualifications, benefits, pay.
Check if we missed any detail: The posting also mentions "Active member of the Data Science community..." etc which we included in responsibilities. Good.
Check if we missed "Provide technical contributions in a fast‑paced team environment to accelerate efforts on building an analytics‑driven product pipeline;" included.
Check "Develop sustainable
for prose. We must not repeat job title. No Job ID etc. Remove boilerplate: cookie/navigation/legal/EEO etc. Also remove application instructions like "YOUR APPLICATION ..." and "To all recruitment agencies..." etc. Also remove location line? It's metadata; we can fold minor metadata into short
or drop it. Probably drop location line. We need preserve all substantive information: role description, tasks, responsibilities, key working relationships, who you are (required qualifications, preferred qualifications), salary range, benefits. We need to structure sections: About the role (intro paragraph), Responsibilities (list), Key Working Relationships maybe part of Responsibilities? Could be separate but we can include under Responsibilities or as its own section. The instruction: use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should follow those headings exactly if content exists. So we need sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay. Possibly Skills separate from Requirements? The posting has Required Qualifications and Preferred Qualifications. Could map Requirements to required qualifications, Qualifications to preferred? Or Skills separate. But we have to decide. We have: Required Qualifications (list), Preferred Qualifications (list). Also there is mention of skills: "Intermediate proficiency in computational skills... Strong proficiency in predictive modeling... Intermediate proficiency in machine learning algorithms... Experience delivering valuable analysis... Strong communication skills". Those could go under Skills. Thus we can have: - About the role: intro paragraph describing role. - Responsibilities: list of tasks and responsibilities (the bullet list under "Your Tasks And Responsibilities"). - Requirements: maybe required qualifications. - Qualifications: maybe preferred qualifications. - Skills: list of skills (computational proficiency, predictive modeling, machine learning, business acumen, communication). - Benefits: list of benefits. - Pay: salary range. We must not include Schedule. We must not include filler like "commensurate with experience". Not present. We must preserve all substantive information. Ensure we include key working relationships? That is part of responsibilities maybe. Could embed in Responsibilities list as an item. The posting includes "Key Working Relationships:" paragraph. We should include that as part of Responsibilities or maybe as its own section but not in allowed headings. Since only allowed headings are those, we should incorporate into Responsibilities. Thus Responsibilities list items: - Maximize the use of large‑scale genomics and metadata to support high‑throughput DNA genotyping and sequencing production and workflow development needs; - Independently perform bioinformatic analysis, computer programming, and experimental design; - Use and maintain advanced bioinformatic pipelines and databases for mining and visualizing large genomic data sets to deliver insights, recommendations, and solutions; - Provide technical contributions in a fast‑paced team environment to accelerate efforts on building an analytics‑driven product pipeline; - Develop sustainable, consumable, accurate, and impactful reporting on analysis inputs, analysis outputs, biological interpretation, business impact, and key performance indicators; - Present compelling, validated stories to all levels of the organization, including peers, senior management, and internal customers, to drive both strategic and operational changes in the business; - Demonstrate a moderate level of autonomy in developing relationships for effective cross‑functional collaboration across multiple organizations and partners on work stream initiatives for the Data Science community. - Active member of the Data Science community to build personal acumen and ability while sharing best practices with others; - Builds relationships and networks within the current function, with guidance as needed to expand networks cross‑functionally; - Interacts most often with Bioinformaticians and Data Scientists within the organization and peer business partners; - Reports to a Precision Genomics Analytics & Insights Lead but independently drives data science projects with key stakeholders spanning functions and countries. We need to keep the semicolons? Probably just plain text. Now Required Qualifications list: - Currently pursuing a Master’s or Ph.D. in a relevant discipline (Data Science, Machine Learning, Electrical/Industrial Engineering, Statistical Genetics, Statistics, Biostatistics, Bioinformatics, Genomics, Computational Biology, Applied Mathematics, Computer Science, or other related quantitative discipline); - Intermediate proficiency in computational skills and experience building data models using R, Python, or other statistical and/or mathematical programming packages; - Strong proficiency in predictive modeling, including comprehension of theory, modeling/identification strategies, and awareness of limitations and pitfalls; - Intermediate proficiency in machine learning algorithms and concepts; - Experience delivering valuable analysis through application of domain knowledge, demonstrating strong business acumen; - Strong communication skills, including the ability to present and deliver complex quantitative analyses in a clear, concise, and actionable manner to extended teams and small groups of key stakeholders. Preferred Qualifications list: - One to two years of experience with machine learning modeling and working with genomics data; - Strong analytical and problem‑solving skills. Skills section: maybe we can combine some of the above but we already have them in qualifications. However we need a Skills section per instruction; we could list skills like: computational skills (R, Python), predictive modeling, machine learning, business acumen, communication. But that duplicates qualifications. Might be okay but we risk duplication. Perhaps we treat Required Qualifications as Requirements, Preferred Qualifications as Qualifications, and Skills as a summary of key skills extracted (like computational skills, predictive modeling, machine learning, business acumen, communication). But that would lose some detail? The instruction says preserve ALL substantive information; we can't omit details. If we put skills as a separate section, we need to include all skill-related info somewhere. Could put them in Skills section and not duplicate elsewhere. Then Requirements and Qualifications could focus on education/experience. Let's parse: Required Qualifications includes education and proficiency statements. Those are both qualifications and skills. But we can split: Requirements: education (currently pursuing Master's/PhD). Qualifications: experience (maybe none). But the posting also has "Preferred Qualifications". Hmm. Better to follow the headings exactly: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay. We need to map content: - About the role: intro paragraph. - Responsibilities: list of tasks and responsibilities (including key working relationships). - Requirements: Required Qualifications (the list). - Qualifications: Preferred Qualifications (the list). - Skills: maybe we can list the specific skill proficiencies mentioned: computational skills (R, Python), predictive modeling, machine learning algorithms, business acumen, communication skills. But those are already in Required Qualifications. However we can still list them; duplication may be okay but risk of repeating info. The instruction says preserve ALL substantive information; repeating is not prohibited but could be considered redundant. However it's safer to not duplicate; we can put skill details under Skills and not repeat them in Requirements/Qualifications. Then Requirements would be just education? But Required Qualifications includes education plus skill proficiencies. If we move skill proficiencies to Skills, we lose them from Requirements unless we also keep them there. But we could keep education in Requirements and move skill proficiencies to Skills. Then Qualifications (Preferred) stays as is. Thus: Requirements (education): Currently pursuing a Master’s or Ph.D. in a relevant discipline (list). Skills: Intermediate proficiency in computational skills and experience building data models using R, Python, or other statistical and/or mathematical programming packages; Strong proficiency in predictive modeling, including comprehension of theory, modeling/identification strategies, and awareness of limitations and pitfalls; Intermediate proficiency in machine learning algorithms and concepts; Experience delivering valuable analysis through application of domain knowledge, demonstrating strong business acumen; Strong communication skills, including the ability to present and deliver complex quantitative analyses in a clear, concise, and actionable manner to extended teams and small groups of key stakeholders. Qualifications (Preferred): One to two years of experience with machine learning modeling and working with genomics data; Strong analytical and problem‑solving skills. That covers all substantive info. Now Benefits: list: health care, vision, dental, retirement, PTO, sick leave, etc (if relevant). Also mention bonus or commission (if relevant). Actually bonus/compensation mentioned under Pay? The posting says: "Employees can expect to be paid a salary of approximately between $22.75 to $47.75. Additional compensation may include a bonus or commission (if relevant). Additional benefits may include health care, vision, dental, retirement, PTO, sick leave, etc (if relevant)." So Pay section: salary range and note about bonus/commission. Benefits section: list of benefits. We must not include filler like "if relevant". It's part of the posting; we keep it. Now About the role: combine first two paragraphs: "In this role within the Precision Genomics group, you will work collaboratively with interdisciplinary scientists, IT, and engineering professionals to optimize DNA genotyping and sequencing workflows and answer key questions that drive decisions for Precision Genomics and partners across Breeding, Biotech, and Product Supply. As an individual contributor on the Precision Genomics Analytics team, you will help build an analytics‑driven product pipeline by applying advanced mathematical models, machine learning algorithms, and operations research techniques, combined with strong business acumen, to deliver insights, recommendations, and solutions." That's it. Now produce HTML fragment:
About the role
...
Responsibilities
- ... ...
Requirements
- Currently pursuing a Master’s or Ph.D. in a relevant discipline (Data Science, Machine Learning, Electrical/Industrial Engineering, Statistical Genetics, Statistics, Biostatistics, Bioinformatics, Genomics, Computational Biology, Applied Mathematics, Computer Science, or other related quantitative discipline);
Skills
- Intermediate proficiency in computational skills and experience building data models using R, Python, or other statistical and/or mathematical programming packages;
- Strong proficiency in predictive modeling, including comprehension of theory, modeling/identification strategies, and awareness of limitations and pitfalls;
- Intermediate proficiency in machine learning algorithms and concepts;
- Experience delivering valuable analysis through application of domain knowledge, demonstrating strong business acumen;
- Strong communication skills, including the ability to present and deliver complex quantitative analyses in a clear, concise, and actionable manner to extended teams and small groups of key stakeholders;
Qualifications
- One to two years of experience with machine learning modeling and working with genomics data;
- Strong analytical and problem‑solving skills.
Benefits
- health care
- vision
- dental
- retirement
- PTO
- sick leave
- etc (if relevant)
Pay
Employees can expect to be paid a salary of approximately between $22.75 to $47.75. Additional compensation may include a bonus or commission (if relevant).
We need to ensure we didn't include Schedule. Good. Check for any boilerplate removed: we removed location line, reference code, contact info, EEO statements, application instructions, etc. We kept all substantive info: role description, responsibilities, key working relationships, required qualifications (education), skills, preferred qualifications, benefits, pay. Check if we missed any detail: The posting also mentions "Active member of the Data Science community..." etc which we included in responsibilities. Good. Check if we missed "Provide technical contributions in a fast‑paced team environment to accelerate efforts on building an analytics‑driven product pipeline;" included. Check "Develop sustainable