Senior Data Scientist

We need to output HTML fragment with sections: About the role? The description includes company description, position description, responsibilities, qualifications, etc. We must use

for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections if posting has real specific content. We need to parse the posting. Content: - Company description: Altamira Technologies has a long and successful history providing innovative solutions throughout the U.S. National Security community. Headquartered in McLean, Virginia, Altamira serves the defense, intelligence and homeland security communities worldwide by focusing on creating innovative solutions leveraging common standards in architecture, data and security. Altamira believes that our people and the culture of our company differentiate us from other companies. - Position: Senior Data Scientist (title not to be used as heading) - Position Location: Camp Lejeune, North Carolina - Position Description: A data scientist will have skills sets of both data analysts and data engineers. Data scientists are responsible for designing, implementing, and maintaining a data pipeline. In addition, data scientists shall interpret and analyze complex sets of data, as well as plan, execute, and manage ML projects with cloud-native platforms and advanced ML solutions. They understand some of the most challenging processes, technologies, and can leverage a vast array of methodologies in the field, such as data mining, natural language programming, and machine learning. Data scientists must have a combination of skills that include programming, mathematical modeling, statistics, and domain knowledge. They must combine an advanced math and statistics background with programming, domain knowledge, and communication skills to analyze data, create applied mathematical models, and present results in a form useful to the organization. They must also be able to understand and manipulate structured and unstructured large data sets, which requires proficiency in distributed SQL programming, relational and non-relational data queries, general programming languages (such as Python and R,) and machine learning techniques. - Experience: list of bullet-like sentences (but they are sentences separated by periods). We need to extract duties/responsibilities. - Education: Bachelor’s degree in a STEM field is required. Master’s degree is preferred in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields. 6 years data science experience Proficient with one or more programming languages (Java, C++, Python, R, etc.). Proficient in Agile Development and Git Operations. Demonstrated experience applying data science methods to real-world data problems. TS/SCI clearance is preferred Minimum SECRET Clearance to start with the willingness and ability to obtain TS/SCI. - Altamira is an Equal Opportunity/Affirmative Action employer... (boilerplate to remove) - We focus on recruiting talented, self-motivated employees that find a way to get things done. Join our team of experts as we engineer national security! (maybe part of About the role? Could be considered company culture.) We need to produce sections: About the role (company description + maybe location?), Responsibilities (duties), Requirements (education, experience, clearance), Skills (programming languages, tools, methodologies), maybe Benefits? Not present. Pay? Not present. Schedule? Not present. We must not repeat job title as heading. We can include location in About the role paragraph. We must not include boilerplate like EEO, etc. We must preserve all substantive information; do not invent or summarize away detail. We need to use

• for any list of duties/requirements/benefits. So for responsibilities we can list bullet points. For requirements we can list bullet points. For skills we can list bullet points. We must not create sections with filler like "commensurate with experience". Not applicable. We need to decide which sections to include. We have content for: - About the role: company description, location, maybe mission. - Responsibilities: designing, implementing, maintaining data pipeline; interpret and analyze complex data; plan, execute, manage ML projects; leverage methodologies; combine advanced math/stats with programming/domain knowledge/communication; understand/manipulate structured/unstructured large data sets; proficiency in distributed SQL, relational/non-relational queries, programming languages, ML techniques. - Experience list: Interpret and analyze data using exploratory mathematical and statistical techniques based on the scientific method; Coordinate research and analytic activities utilizing various data points (unstructured and structured) and employ programming to clean, massage, and organize the data; Experiment against data points, provide information based on experiment results and provide previously undiscovered solutions to command data challenges; Coordinate with Data Engineers to build Data environments providing data identified by other data professionals; Apply and develop scientific methodology, statistics, and algorithms to discover and frame relevant problems, hypotheses, and opportunities; Develop predictive and prescriptive modeling, natural language processing (NLP), Robotic Process Automation (RPA), text mining and processing, clustering, forecasting methods, and other advanced statistical techniques; Design and automate processes to facilitate the manipulation and analysis of data; Manage and integrate data across dissimilar data sets; Analyze large-scale structured and unstructured data; Use frameworks such as Spark and Hadoop to conduct large-scale data processing; Perform statistical modeling and create data visualizations using products like Tableau, Microsoft Power BI and R Shiny; Research, design, and implement algorithms to solve complex problems; Program using R, Python (NumPy, SciPy, Pandas) or similar analytical languages; Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and Snowflake; Communicate complex concepts and hypothesis to a non-technical audience through digital storytelling. These are responsibilities/experience; could be under Responsibilities. - Education/Qualifications: Bachelor’s degree in a STEM field required; Master’s degree preferred in specific fields; 6 years data science experience; Proficient with one or more programming languages (Java, C++, Python, R, etc.); Proficient in Agile Development and Git Operations; Demonstrated experience applying data science methods to real-world data problems; TS/SCI clearance preferred; Minimum SECRET Clearance to start with willingness and ability to obtain TS/SCI. We could split into Qualifications (education + experience) and Skills (programming languages, tools, methodologies). But the instructions say use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we can have Requirements (maybe combine education and experience) and Skills (technical skills). Or we could have Qualifications and Skills separate. We need to decide based on content. We have education, experience, clearance (these are qualifications). We have programming languages, Agile/Git, tools (Spark, Hadoop, Tableau, Power BI, R Shiny, Databricks, IBM Cloud Pak, Cloudera, Snowflake), methodologies (NLP, RPA, text mining, clustering, forecasting, etc.). Those could be Skills. Thus we can have:

  About the role

  ... company description and location.

  Responsibilities

  • ... each responsibility bullet.

  Qualifications

  • ... education, experience, clearance.

  Skills

  • ... programming languages, tools, methodologies.
  We should not include Benefits, Pay, Schedule as they are not present. We must not repeat job title as heading. We must preserve all substantive information: need to include all bullet points exactly as given, not summarizing. We need to ensure we don't lose any detail. Let's extract each piece. Company description paragraph: "Altamira Technologies has a long and successful history providing innovative solutions throughout the U.S. National Security community. Headquartered in McLean, Virginia, Altamira serves the defense, intelligence and homeland security communities worldwide by focusing on creating innovative solutions leveraging common standards in architecture, data and security. Altamira believes that our people and the culture of our company differentiate us from other companies." Add location: "Position Location: Camp Lejeune, North Carolina". Could be included in same paragraph: maybe after company description: "The position is located in Camp Lejeune, North Carolina." Now responsibilities: we have the Position Description paragraph plus the Experience list. We need to break into bullet points. The Position Description paragraph contains multiple sentences; we could split into bullet points for each distinct responsibility. But we must preserve all substantive information; we can keep as prose or bullet list. The instruction: Use
  • for any list of duties/requirements/benefits. So if we have a list, we should use
    • . The Position Description paragraph is not explicitly a list but contains multiple duties. Safer to convert each sentence into a bullet. Let's list responsibilities from Position Description: - Designing, implementing, and maintaining a data pipeline. - Interpret and analyze complex sets of data. - Plan, execute, and manage ML projects with cloud-native platforms and advanced ML solutions. - Leverage a vast array of methodologies in the field, such as data mining, natural language programming, and machine learning. - Combine programming, mathematical modeling, statistics, and domain knowledge. - Combine an advanced math and statistics background with programming, domain knowledge, and communication skills to analyze data, create applied mathematical models, and present results in a form useful to the organization. - Understand and manipulate structured and unstructured large data sets, which requires proficiency in distributed SQL programming, relational and non-relational data queries, general programming languages (such as Python and R,) and machine learning techniques. Now the Experience list items (these are more detailed responsibilities/experience). We could treat them as responsibilities as well. But to avoid duplication, we could merge them under Responsibilities as bullet points. Let's list each Experience bullet: - Interpret and analyze data using exploratory mathematical and statistical techniques based on the scientific method. - Coordinate research and analytic activities utilizing various data points (unstructured and structured) and employ programming to clean, massage, and organize the data. - Experiment against data points, provide information based on experiment results and provide previously undiscovered solutions to command data challenges. - Coordinate with Data Engineers to build Data environments providing data identified by other data professionals. - Apply and develop scientific methodology, statistics, and algorithms to discover and frame relevant problems, hypotheses, and opportunities. - Develop predictive and prescriptive modeling, natural language processing (NLP), Robotic Process Automation (RPA), text mining and processing, clustering, forecasting methods, and other advanced statistical techniques. - Design and automate processes to facilitate the manipulation and analysis of data. - Manage and integrate data across dissimilar data sets. - Analyze large-scale structured and unstructured data. - Use frameworks such as Spark and Hadoop to conduct large-scale data processing. - Perform statistical modeling and create data visualizations using products like Tableau, Microsoft Power BI and R Shiny. - Research, design, and implement algorithms to solve complex problems. - Program using R, Python (NumPy, SciPy, Pandas) or similar analytical languages. - Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and Snowflake. - Communicate complex concepts and hypothesis to a non-technical audience through digital storytelling. We should ensure we don't duplicate similar items (like "interpret and analyze data" appears both in Position Description and Experience list). Might be okay to keep both but could be considered duplication. The instruction: "Remove duplicated lines". So we should remove duplicated lines. The phrase "Interpret and analyze data using exploratory mathematical and statistical techniques based on the scientific method." is similar to "Interpret and analyze complex sets of data." Not exact duplicate but similar. Might be considered duplicated? Safer to keep both as they are slightly different. However "Interpret and analyze complex sets of data." is a generic statement; the Experience bullet adds more detail. We could keep both but maybe it's okay. We also have "Design and automate processes to facilitate the manipulation and analysis of data." similar to "Designing, implementing, and maintaining a data pipeline." Not exact duplicate. We'll keep them. Now Qualifications: education, experience, clearance. List: - Bachelor’s degree in a STEM field is required