Principal Data Science Manager
United States
We are seeking a Principal Data Science Manager with advanced knowledge of both traditional and cutting-edge machine learning (ML) and artificial intelligence (AI) technologies, as well as extensive experience creating data-driven solutions. As a member of our team, you will collaborate to find solutions to challenging issues with important clients and high-impact data scientists. You will inform stakeholders about trends and cutting-edge AI solutions. In order to implement business solutions, you will collaborate cross-functionally with a number of teams, including engineering groups, product teams, and program management.
AccountabilitiesPersonnel Administration
Managers model, mentor, and show compassion in order to empower and hold people accountable.
Model: Adopt our beliefs, live out our culture, and put our leadership tenets into action.
Coach: Establish team goals and expectations; Promote success across borders; Assist team in growing and changing.
Care: Draw in and hold onto exceptional talent; Ascertain the potential and goals of each person; Contribute to the development of others.
Managers model, mentor, and show compassion in order to empower and hold people accountable.
Model: Adopt our beliefs, live out our culture, and put our leadership tenets into action.
Coach: Establish team goals and expectations; Promote success across borders; Assist team in growing and changing.
Care: Draw in and hold onto exceptional talent; Ascertain the potential and goals of each person; Contribute to the development of others.
oversees data-science teams or projects to ensure they are valuable and in line with business needs.
establishes and conveys the team's and the project's technical direction and strategy. This entails being aware of the project's objectives, market trends, and technical delivery context in order to inform choices, maintain focus, and guarantee alignment with corporate goals.
Provide technical direction, make best practice suggestions, and facilitate team agreements pertaining to best practices. provides team members with assistance when needed.
guarantees that the project deliverables meet the necessary standards for quality. This entails defining expectations clearly and supervising execution to guarantee standards are met.
carries out and supervises the creation of high-quality data and pertinent hypotheses by doing in-depth exploratory data analysis on big, complicated datasets in order to find patterns, trends, and linkages. In order to achieve good data quality and dependability, this procedure includes applying statistical techniques like regression analysis and hypothesis testing in addition to data cleaning, preprocessing, and handling missing data, outliers, and anomalies.
creates and uses best practices and ML/AI tools to deliver dependable, scalable, and morally sound data-driven solutions. This entails creating experimental designs and putting hypothesis testing into practice in order to look into the feasibility and veracity of new ideas and adjustments.
Assessment
Work together with stakeholders to comprehend the project's precise aims and objectives, and assist in creating a structured method of assessing the systems' performance in relation to them. Finding metrics and key performance indicators (KPIs) that support the organization's goals and establishing connections between them and the traditional performance indicators for the models utilised by the system may be necessary to achieve this.
Knowledge of Industry and Research and Identification of Opportunities
exchanges industry data science information, encourages progress, and offers criticism.
Debugging and Coding
oversees the creation of solutions and writes, evaluates, and debugs code for challenging tasks.
Commercial Administration
leads IP improvement and data-science alliances.
A focus on the customer or partner
offers solutions and insights that are focused on the needs of the customer by comprehending the business, the product, the data, and the audience.
Conscientious AI
Respects Microsoft's AI Customer Promise
Essential Requirements:
A PhD in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or a related field AND 5+ years of experience in data science (managing structured and unstructured data, applying statistical techniques, and reporting results) OR a Master's degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or a related field AND 7+ years of experience in data science (managing structured and unstructured data, applying statistical techniques, and reporting results) OR a Bachelor's degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or a related field AND 10+ years of experience in data science (managing structured and unstructured data
three plus years of experience managing people.
five or more years of experience providing professional services, handling projects, interacting with customers, and/or consulting.
8+ years of expertise in data science (such as handling structured and unstructured data, using statistical techniques, and presenting results) AND a doctorate in data science, mathematics, statistics, econometrics, economics, operations research, computer science, or a related subject
Alternatively, ten or more years of experience in data science (such as handling organized and unstructured data, using statistical techniques, and presenting results) AND a master's degree in data science, mathematics, statistics, econometrics, economics, operations research, computer science, or a related discipline
OR 12+ years of experience in data science (managing structured and unstructured data, applying statistical techniques, and reporting results), OR equivalent experience, AND a bachelor's degree in data science, mathematics, statistics, econometrics, economics, operations research, computer science, or a related field.
shown expertise in the field in one or more of the following areas: Media and Communications [MNC], Energy and Sustainability [ENS], Manufacturing and Supply Chain [MSC], and Automotive, Mobility, and Transportation [AMT]
five plus years of experience managing people.
Salary - USD $133,600 - $256,800 per year
