Marketing Data Scientist Role Overview
The Marketing Data Scientist role is a contract position classified under internal temporary worker employment, with a 2-year contract duration. It sits within the Advanced Analytics group at HP, where the work centers on applying advanced data science skills to a range of marketing analytics problems. The role is designed for someone who can contribute both technically and strategically, while helping develop innovative solutions within a complex environment. It also calls for a colleague who is comfortable leading complex projects and presenting to senior leadership.
At a high level, this position combines marketing analytics, technical model development, and application-oriented project work. The successful candidate is expected to bring strong experience in R and Python, along with at least 3 years of experience. The work also includes experience in multi-touch attribution and marketing mix modeling, from model development to optimization. In addition, the role includes helping with project architecture and building applications using frameworks such as Shiny, Flask, or React.
Employment Type and Team Context
This role is defined first by its employment structure and organizational setting. It is a contract position and is classified as internal temporary worker employment. The contract duration is 2 years, which gives the position a clear time frame while still allowing for substantial project involvement. Within that period, the work is embedded in the Advanced Analytics group at HP, which frames the role as part of a specialized analytics environment.
The team context matters because the position is not described as a general data science role. Instead, it is specifically tied to marketing analytics and the application of advanced data science skills to solve a variety of problems. That means the work is likely to involve both technical depth and practical business relevance. The role is also positioned within a group that supports innovative solutions, which suggests that the work is expected to be both analytical and forward-looking.
The combination of contract structure, internal temporary worker classification, and a 2-year duration gives the role a defined scope. At the same time, the description emphasizes meaningful contribution, leadership of complex projects, and communication with senior leadership. This makes the position suitable for someone who can work independently while also contributing to broader team goals. The setting within Advanced Analytics at HP provides the context for that balance.
Standout fact: The role is a Marketing Data Scientist contract position under internal temporary worker employment with a 2-year contract duration.
The role also stands out because it is not limited to one narrow task. It brings together analytics, model work, application development, and leadership-facing communication. That combination makes the position broader than a single-model or single-tool assignment. It is centered on marketing analytics, but the responsibilities extend into architecture and solution development as well.
Technical Skills and Experience Expectations
The technical profile for this role is clearly defined. The successful candidate should have strong skills in R and Python, which are identified as key tools for the work. In addition, the role requires at least 3 years of experience. These expectations indicate that the position is intended for someone who already has a solid foundation and can contribute without needing to build core technical capability from the ground up.
Beyond general programming ability, the role specifically calls for experience in multi-touch attribution and marketing mix modeling. The description makes clear that this experience should cover the full process, from model development to optimization. That means the work is not limited to building models in isolation; it also includes improving and refining them for practical use. The emphasis on optimization suggests a focus on making models more effective and useful in marketing analytics contexts.
The role also implies a need for someone who can work across technical and applied dimensions. Strong technical skills are important, but they are paired with the ability to solve a variety of problems in marketing analytics. This means the candidate should be comfortable using data science methods in a way that supports real project needs. The description does not separate technical work from business application; instead, it presents them as connected parts of the same role.
- R experience
- Python experience
- At least 3 years of experience
- Experience in multi-touch attribution
- Experience in marketing mix modeling
- Ability to work from model development to optimization
The technical expectations also suggest a role that values end-to-end ownership. A candidate with the right background would be expected to move from analysis into model building and then into improvement work. Because the description highlights both development and optimization, the role appears to reward practical, iterative problem-solving. That makes the technical scope broad, but still clearly centered on marketing analytics.
Marketing Analytics Focus and Core Problem Areas
The central purpose of the role is to apply advanced data science skills to a variety of problems in marketing analytics. This focus gives the position a clear domain orientation. Rather than working on general-purpose analytics alone, the role is aimed at marketing-related challenges that benefit from modeling, optimization, and structured analytical thinking. The description does not list specific campaigns or business units, so the scope should be understood in the broader sense of marketing analytics work.
Two specific areas are named as important: multi-touch attribution and marketing mix modeling. These are presented as core experience areas, and the description makes clear that the candidate should have worked in both. The role expects familiarity with the full lifecycle of these efforts, including model development and optimization. That means the work is not only about understanding the methods, but also about applying them in a way that supports better outcomes.
The phrase “a variety of problems” is important because it shows that the role is not limited to one repeated task. Instead, the data scientist will likely be expected to address different marketing analytics needs as they arise. This can involve adapting advanced data science skills to changing project requirements. The role therefore combines specialization in marketing analytics with flexibility in problem-solving.
Areas emphasized in the role
- Marketing analytics as the main domain
- Multi-touch attribution as a required experience area
- Marketing mix modeling as a required experience area
- Model development as part of the work
- Optimization as part of the work
The emphasis on these areas suggests that the role is built around analytical methods that support marketing decision-making. It also shows that the candidate is expected to contribute in a way that is both technical and practical. Since the description highlights innovative solutions, the work likely involves applying these methods thoughtfully rather than mechanically. The role is therefore best understood as a marketing analytics position with strong data science depth.
Project Architecture and Application Development
In addition to analytics and modeling, the role includes support for project architecture. This is an important part of the description because it expands the position beyond analysis alone. The candidate is expected to help shape how projects are organized and how solutions are built. That means the role includes a structural or architectural dimension, not just model execution.
The description also specifies the development of applications using frameworks such as Shiny, Flask, or React. These frameworks are named as examples of the tools that may be used in the role. Their inclusion shows that the position may involve building applications that support analytics work or help deliver solutions in a usable format. The candidate should therefore be comfortable contributing to application development as part of the broader project effort.
This application-oriented element is closely connected to the role’s focus on innovative solutions. Building applications can help translate analytical work into something more accessible or operational. The description does not provide specific application use cases, so it is best to stay with the stated expectation: helping with project architecture and application development. That combination suggests a role that bridges data science and software-oriented implementation.
Frameworks named in the role
- Shiny
- Flask
- React
The mention of these frameworks also reinforces the need for technical versatility. A candidate in this role is not only expected to analyze data and build models, but also to contribute to the way solutions are delivered. That makes the position especially relevant for someone who can move between analytics and application development. The project architecture component adds another layer to the role’s overall scope.
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Leadership, Innovation, and Communication
The role places strong emphasis on contribution beyond technical execution. The new colleague is expected to contribute to the development of innovative solutions, which signals a forward-looking and problem-solving mindset. This is not framed as a passive support role. Instead, the description suggests active involvement in shaping what gets built and how it helps address marketing analytics needs.
Another important expectation is the ability to lead complex projects. That language indicates responsibility, coordination, and the ability to manage work that is not simple or routine. The role therefore appears to require someone who can handle complexity and guide efforts through to completion. This leadership aspect is paired with the technical and architectural responsibilities already described.
The candidate must also be comfortable presenting to senior leadership. This is a key communication requirement because it shows that the role includes interaction with high-level stakeholders. The ability to present clearly and confidently is therefore part of the job, alongside analytical and development work. The description does not specify presentation topics, but it does make clear that communication at a senior level is expected.
Standout fact: The role expects someone who can lead complex projects and be comfortable presenting to senior leadership.
These expectations make the role multidimensional. The candidate is expected to be technically strong, analytically capable, and able to communicate effectively in leadership settings. That combination is important because the role sits at the intersection of data science, marketing analytics, and solution development. It is therefore a position where both execution and influence matter.
The innovation focus also connects back to the broader Advanced Analytics setting. The role is not only about maintaining existing work; it is about helping develop new solutions. That makes the position suitable for someone who enjoys building, improving, and explaining analytical work in a collaborative environment. The leadership and communication requirements help ensure that the work can be translated into action.
Role Summary for Search and Quick Reference
For quick reference, the Marketing Data Scientist role is a contract position within internal temporary worker employment at HP, with a 2-year contract duration. It is located in the Advanced Analytics group and focuses on solving a variety of problems in marketing analytics. The role requires strong technical skills in R and Python, at least 3 years of experience, and experience in multi-touch attribution and marketing mix modeling.
The position also includes helping with project architecture and developing applications using frameworks such as Shiny, Flask, or React. In addition, the successful candidate is expected to contribute to innovative solutions, lead complex projects, and present to senior leadership. These combined responsibilities make the role broad, technical, and communication-oriented. The description presents a candidate who can work across analytics, development, and leadership-facing collaboration.
Frequently Asked Questions
What type of position is the Marketing Data Scientist role?
The role is a contract position and is classified under internal temporary worker employment. It is also described with a 2-year contract duration. These details define the employment structure clearly and show that the role has a set time frame.
Which team does the role belong to?
The position is within the Advanced Analytics group at HP. The role is centered on applying advanced data science skills to marketing analytics problems. This team context is part of what shapes the scope of the work.
What technical skills are required?
The description highlights strong technical skills in R and Python. It also states that the successful candidate should have at least 3 years of experience. These are the main technical and experience requirements named in the content.
What marketing analytics experience is expected?
The role calls for experience in multi-touch attribution and marketing mix modeling. It also specifies that this experience should cover model development through optimization. The focus is on practical, end-to-end work in marketing analytics.
Does the role include application development?
Yes. The description says the candidate will help with project architecture and the development of applications using frameworks such as Shiny, Flask, or React. This shows that the role includes both analytics and application-oriented work.
What leadership and communication expectations are included?
The new colleague is expected to contribute to innovative solutions, lead complex projects, and be comfortable presenting to senior leadership. These expectations show that the role involves more than technical execution. Communication and leadership are part of the position.
Conclusion
The Marketing Data Scientist role at HP brings together advanced analytics, marketing modeling, application development, and leadership communication in one contract position. It is defined as an internal temporary worker role with a 2-year duration, based in the Advanced Analytics group. The position calls for strong skills in R and Python, at least 3 years of experience, and hands-on experience in multi-touch attribution and marketing mix modeling. It also includes helping with project architecture, building applications, leading complex projects, and presenting to senior leadership. Overall, the role is structured for someone who can contribute across technical, analytical, and collaborative dimensions.
