Sr. Data Scientist I (hybrid)

We need to produce HTML fragment with headings

for sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. Must not repeat job title as heading. Must not include Job ID etc. Must preserve all substantive info, no invention. Remove boilerplate, navigation, legal, EEO, equal-opportunity, scam-warning, duplicated lines, application instructions. We need to parse the posting. Content: - Title: Sr. Data Scientist I (hybrid) Federated Hermes Career Opportunity #9777 (ignore ID) - "We have an exciting opportunity for a Sr. Data Scientist I, located in Pittsburgh, PA." - "What You’ll Do" (section heading) - This is a full-stack data science position that works across the Azure Cloud ecosystem including Microsoft Foundry, Databricks, and frontier models like OpenAI and Claude. The Senior Data Scientist I will drive the full data science lifecycle, from strategy and data preparation through algorithm development (including generative AI and agentic approaches) to communicating results in a way anyone can understand. A proactive, creative, curious mindset and a drive to grow your own skills will go a long way. - "The Expertise We’re Looking For" (list of requirements) - Bachelor’s Degree in STEM (science, technology, engineering, math) related field or a similar quantitative analytics field; Master’s Degree in STEM (science, technology, engineering, math) related field or a similar quantitate analytics field preferred - Minimum 2–4 years of professional experience with data science concepts, data transformation, algorithm development, and computational tools (e.g., Python, Spark/PySpark, SQL, and cloud-based data platforms such as Databricks) - Professional experience manipulating and analyzing various types of data using Python, Spark, or similar software - Experience with varying database structures and working with large datasets - Proficiency with developing data visualization technology and capabilities (i.e. Power BI) in a professional setting - Experience with a variety of data products that complement model/algorithm development and productionizing (e.g., Pandas, Azure AI Services, Databricks, Jupyter Notebooks) - Experience working with LLM/generative AI tooling and APIs (e.g., OpenAI, Anthropic Claude, LangChain) to build AI-powered data products - Experience with data tools and advanced analytic capabilities in the Azure cloud ecosystem, including Microsoft Foundry is preferred - Experience productionizing data products and/or deploying machine learning or generative AI pipelines is preferred - Strong problem-solving skills including ability to debug, troubleshoot, and design solutions to complex data product issues - Analytical agility including ability to quickly learn and apply new modeling, machine learning, and AI techniques as they rapidly evolve - Familiarity with software engineering best practices (e.g., version control, code review) to support production-quality data science work - **The experience level of the candidate will determine level of position as Sr. Data Scientist I or Sr. Data Scientist II** (maybe note but not a requirement; could be included in Requirements or Qualifications.) - "Our Investment in You" (benefits) - We believe our employees are our most important asset! Therefore, we offer benefits programs designed to help you and your family thrive, training programs to advance your professional development and opportunities for you to give back to the community. Our offerings include: - A competitive total compensation package, including bonus programs designed to recognize and incentivize our employees to do their best every day - Time off programs including paid vacation, parental leave and a volunteer day to help you stay healthy and connected to the things that are important - Opportunities to expand your professional network within the firm and the community through participation in programs such as the Women in Investing Employee Resource Business Group and the University Ambassador Program. - Location: Pittsburgh, PA (Hybrid in-office work schedule) - Hours: 8:30 pm -5:00 pm (looks odd: maybe 8:30 am -5:00 pm? but it's given as 8:30 pm -5:00 pm; we must preserve as is.) - About Federated Hermes (company description) - maybe not needed as a section? Could be considered "About the company" but not in list of allowed headings. The allowed headings are About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We can map content accordingly. We need to decide which sections to include. - About the role: Could include the introductory paragraph about opportunity and location? The "What You’ll Do" is responsibilities. So About the role could be a brief overview: "We have an exciting opportunity for a Sr. Data Scientist I, located in Pittsburgh, PA. This is a full-stack data science position that works across the Azure Cloud ecosystem including Microsoft Foundry, Databricks, and frontier models like OpenAI and Claude." But we must not invent or summarize away detail. We can keep the sentences as is. Better: Use "About the role" for the initial description: "We have an exciting opportunity for a Sr. Data Scientist I, located in Pittsburgh, PA. This is a full-stack data science position that works across the Azure Cloud ecosystem including Microsoft Foundry, Databricks, and frontier models like OpenAI and Claude. The Senior Data Scientist I will drive the full data science lifecycle, from strategy and data preparation through algorithm development (including generative AI and agentic approaches) to communicating results in a way anyone can understand. A proactive, creative, curious mindset and a drive to grow your own skills will go a long way." But that includes responsibilities. However we also have a separate Responsibilities section. We could split: About the role: brief overview (location, hybrid). Responsibilities: the detailed duties. Let's extract: - Location and hybrid: "We have an exciting opportunity for a Sr. Data Scientist I, located in Pittsburgh, PA." and later "Location: Pittsburgh, PA (Hybrid in-office work schedule)". So we can combine. - About the role: maybe just the sentence about opportunity and location. - Responsibilities: The "What You’ll Do" paragraph. - Requirements: The list under "The Expertise We’re Looking For" (including education, experience, etc.) - Qualifications: maybe separate education vs experience? But we can combine. However we need to decide if we need both Requirements and Qualifications sections. The instruction: use headings for those sections if there is real specific content. We could put education under Qualifications, experience under Requirements. But we must not invent content. We have both education and experience listed together. Could split: Qualifications: Bachelor’s/Master’s degree preferences. Requirements: experience, skills, etc. That seems reasonable. - Skills: maybe list specific technical skills: Python, Spark/PySpark, SQL, Databricks, Power BI, Pandas, Azure AI Services, Jupyter Notebooks, OpenAI, Anthropic Claude, LangChain, Microsoft Foundry, version control, code review. Could be a separate Skills section. - Benefits: from "Our Investment in You" bullet list. - Pay: Not explicitly stated; only "competitive total compensation package" but no specific numbers. The instruction: never create Pay/Schedule/Benefits sections unless the posting actually states them. It says "competitive total compensation package" but that's vague; does that count as stating Pay? It's not a specific number or range. The instruction says: never emit a heading followed by filler/placeholder text (e.g., "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless the posting actually states them. "competitive total compensation package" is vague but still states that there is a competitive total compensation package. Is that considered stating Pay? It's not a specific figure but it's a statement about compensation. The instruction says "unless the posting actually states them". It does state that there is a competitive total compensation package, which is a statement about pay/benefits. However the example of filler includes "commensurate with experience". That's similar to "competitive total compensation package". Might be considered filler. Safer to not include Pay section because it's not a specific number or range. The instruction: "never create Pay/Schedule/Benefits sections unless the posting actually states them." It does state "competitive total compensation package". That is a statement about pay, albeit generic. But the instruction also says "Prefer a few substantive sections over many thin ones." So maybe we can incorporate compensation info into Benefits section (since benefits includes compensation). Actually Benefits section already includes "A competitive total compensation package, including bonus programs". So we can put that under Benefits. So we don't need a separate Pay section. - Schedule: we have Hours: 8:30 pm -5:00 pm and Location hybrid schedule. That is schedule info. So we can include a Schedule section with that. Thus sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Schedule. We must not include Pay. Now we need to format with

headings,

• for lists,

  for prose. We must preserve all substantive information, not invent or summarize away detail. So we need to keep all bullet points exactly as given (maybe minor formatting). Ensure we don't drop any. Let's extract each piece. About the role: - "We have an exciting opportunity for a Sr. Data Scientist I, located in Pittsburgh, PA." - Could also include "This is a full-stack data science position that works across the Azure Cloud ecosystem including Microsoft Foundry, Databricks, and frontier models like OpenAI and Claude. The Senior Data Scientist I will drive the full data science lifecycle, from strategy and data preparation through algorithm development (including generative AI and agentic approaches) to communicating results in a way anyone can understand. A proactive, creative, curious mindset and a drive to grow your own skills will go a long way." But that is more responsibilities. However we could keep it in About the role as overview. But then Responsibilities would be empty. Better to split: About the role: location and hybrid mention. Responsibilities: the "What You’ll Do" paragraph. Thus About the role: "We have an exciting opportunity for a Sr. Data Scientist I, located in Pittsburgh, PA." plus maybe "Location: Pittsburgh, PA (Hybrid in-office work schedule)". But that duplicates. We'll combine: "We have an exciting opportunity for a Sr. Data Scientist I, located in Pittsburgh, PA (Hybrid in-office work schedule)." That captures location and hybrid. Now Responsibilities: The "What You’ll Do" paragraph exactly: "This is a full-stack data science position that works across the Azure Cloud ecosystem including Microsoft Foundry, Databricks, and frontier models like OpenAI and Claude. The Senior Data Scientist I will drive the full data science lifecycle, from strategy and data preparation through algorithm development (including generative AI and agentic approaches) to communicating results in a way anyone can understand. A proactive, creative, curious mindset and a drive to grow your own skills will go a long way." We need to keep that as a

  . Now Requirements: maybe the experience and technical expertise list (excluding education). Let's list: - Minimum 2–4 years of professional experience with data science concepts, data transformation, algorithm development, and computational tools (e.g., Python, Spark/PySpark, SQL, and cloud-based data platforms such as Databricks) - Professional experience manipulating and analyzing various types of data using Python, Spark, or similar software - Experience with varying database structures and working with large datasets - Proficiency with developing data visualization technology and capabilities (i.e. Power BI) in a professional setting - Experience with a variety of data products that complement model/algorithm development and productionizing (e.g., Pandas, Azure AI Services, Databricks, Jupyter Notebooks) - Experience working with LLM/generative AI tooling and APIs (e.g., OpenAI, Anthropic Claude, LangChain) to build AI-powered data