Data Scientist III

We need to output HTML fragment with headings

for sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. The posting includes description of role (responsibilities), qualifications, required tasks (maybe responsibilities). No explicit Benefits, Pay, Schedule. So we should include About the role? The intro paragraph: "Reflexive Concepts is seeking a skilled Data Scientist III to join our growing team! The Data Scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows." That's about the role. Could be "About the role". Then responsibilities: many bullet points after "Required:" and later list of tasks. Those are responsibilities. Qualifications: the bullet list about degrees and experience. Skills: maybe not separate; could combine with qualifications? But we can have Skills section if there are specific skills listed: e.g., MLOPS, data science background, data visualizations, working with SMEs, etc. However many of those are responsibilities. The instruction: prefer few substantive sections over many thin ones. So we could have About the role, Responsibilities, Qualifications. Possibly Skills if distinct. But we can embed skills within responsibilities or qualifications. Let's decide: About the role (intro paragraph). Responsibilities (list of duties). Qualifications (education/experience). No Benefits/Pay/Schedule. Use

• for any list. Use

  for prose. We need to preserve all substantive information, not invent or summarize away detail. Must not repeat job title as heading. Must not include Job ID etc. Remove boilerplate. We need to extract the responsibilities list: after "Required:" there is a long list of items each starting with a verb. Also earlier there is list of tasks in the intro? Actually the intro sentence includes many tasks separated by semicolons. Those could be part of responsibilities as well. But we can combine. We need to ensure we don't lose any detail. Let's parse the posting: First paragraph: "Reflexive Concepts is seeking a skilled Data Scientist III to join our growing team! The Data Scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows." That's the role description. Then "Qualifications" heading appears in the posting: "Qualifications Bachelor's degree or higher from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science).An additional four (4) years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a Bachelor's degree.A Master’s Degree from an accredited college or university in a quantitative discipline can be substituted for two (2) years of experience for a total of eight (8) years of experience required.A Doctoral Degree from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience for a total of six (6) years of experience required.A minimum of ten (10) years of experience in two (2) or more of the following: designing/implementing machine learning, data mining, advanced analytical algorithms, advanced statistical analysis, artificial intelligence, or software engineering with data analysis software such as R, Python, SAS, or MATLAB. Required: Significant MLOPS and Data Science background" Then after that there is a list of responsibilities (starting with "Produce data visualizations..."). Let's capture that list exactly as given: - Produce data visualizations that provide insight into dataset structure and meaning - Work with subject matter experts (SMEs) to identify important information in raw data and develop scripts that extract this information from a variety of data formats (e.g., SQL tables, structured metadata, network logs) - Incorporate SME input into feature vectors suitable for analytic development and testing - Translate customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypes - Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics - Develop statistical tests to make data-driven recommendations and decisions - Develop experiments to collect data or models to simulate data when required data are unavailable - Develop feature vectors for input into machine learning algorithms - Identify the most appropriate algorithm for a given dataset and tune input and model parameters - Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices) - Oversee the development of individual analytic efforts and guide team in analytic development process - Guide analytic development toward solutions that can scale to large datasets - Partner with software engineers and cloud developers to develop production analytics - Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation - Lead a team of data scientists in the development of multiple analytic efforts - Work with customers and SMEs to define analytic requirements and guide the team in formulating analytics that meet requirements - Guide the transition of prototyped analytics to production system - Understand emerging machine learning and pattern recognition algorithms and guide a team of data scientists in integrating state-of-the-art algorithms into solutions - Delegate analysis responsibilities to one or more team members and monitor performance We need to output as

  • items. Now the qualifications paragraph: It's a bit dense. We need to preserve all info. Could break into

    with sentences. Could also make a

    for the bullet points about degree substitution etc. But the instruction: Use
    • for any list of duties/requirements/benefits. Qualifications is a list of requirements; we could format as
      . However the qualifications paragraph includes sentences that are not clearly bullet-separated but we can split by periods. But better to keep as prose? The rule: Use
      • for any list of duties/requirements/benefits. So if we treat qualifications as a list of requirements, we should use
        . However the content includes multiple sentences that are not explicitly bullet points but we can convert each requirement into a list item. Let's parse: - Bachelor's degree or higher from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science). - An additional four (4) years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a Bachelor's degree. - A Master’s Degree from an accredited college or university in a quantitative discipline can be substituted for two (2) years of experience for a total of eight (8) years of experience required. - A Doctoral Degree from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience for a total of six (6) years of experience required. - A minimum of ten (10) years of experience in two (2) or more of the following: designing/implementing machine learning, data mining, advanced analytical algorithms, advanced statistical analysis, artificial intelligence, or software engineering with data analysis software such as R, Python, SAS, or MATLAB. - Required: Significant MLOPS and Data Science background We could keep as
        . That seems appropriate. Now responsibilities: we have the intro paragraph (role description) and the list after "Required:" (which is actually responsibilities). The intro paragraph could be considered "About the role". The list after "Required:" are responsibilities/duties. We could combine them into a single Responsibilities section, but we also have About the role separate. The instruction: Prefer a few substantive sections over many thin ones. So maybe we combine About the role and Responsibilities into one section? But we have headings defined: About the role, Responsibilities, etc. We could have About the role (short paragraph) and Responsibilities (the detailed list). That's two sections. That's fine. We must not repeat job title as heading. So we won't. Now we need to output only HTML fragment, no /, no markdown. Thus:

        About the role

        Reflexive Concepts is seeking a skilled Data Scientist III to join our growing team! The Data Scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.

        Responsibilities

        • Produce data visualizations that provide insight into dataset structure and meaning
        • Work with subject matter experts (SMEs) to identify important information in raw data and develop scripts that extract this information from a variety of data formats (e.g., SQL tables, structured metadata, network logs)
        • Incorporate SME input into feature vectors suitable for analytic development and testing
        • Translate customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypes
        • Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics
        • Develop statistical tests to make data-driven recommendations and decisions
        • Develop experiments to collect data or models to simulate data when required data are unavailable
        • Develop feature vectors for input into machine learning algorithms
        • Identify the most appropriate algorithm for a given dataset and tune input and model parameters
        • Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices)
        • Oversee the development of individual analytic efforts and guide team in analytic development process
        • Guide analytic development toward solutions that can scale to large datasets
        • Partner with software engineers and cloud developers to develop production analytics
        • Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation
        • Lead a team of data scientists in the development of multiple analytic efforts
        • Work with customers and SMEs to define analytic requirements and guide the team in formulating analytics that meet requirements
        • Guide the transition of prototyped analytics to production system
        • Understand emerging machine learning and pattern recognition algorithms and guide a team of data scientists in integrating state-of-the-art algorithms into solutions
        • Delegate analysis responsibilities to one or more team members and monitor performance

        Qualifications

        • Bachelor's degree or higher from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science).
        • An additional four (4) years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a Bachelor's degree.
        • A Master’s Degree from an accredited college or university in a quantitative discipline can be substituted for two (2) years of experience for a total of eight (8) years of experience required.
        • A Doctoral Degree from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience for a total of six (6) years of experience required.
        • A minimum of ten (10) years of