Lead to Cash Partner Managed Services Data Scientist

L2C Partner Managed Services Data Scientist

Description -

Are you ready to imagine the future and help us transform? Lead-to-Cash is a process reengineering program tasked to dramatically simplify and streamline HP's processes from lead generation to cash collection; sponsored by HP’s ELT (Executive Leadership Team). Effective management of the Lead to Cash process will lead to increased efficiency, better customer experience, and increased revenue for the organization.

The Lead to Cash Partner Managed Services Data Scientist will be part of the Partner Managed Services program that, in close collaboration with different businesses organizations and markets, will support building the right programs to incubate, scale and accelerate our Managed Services business through the channel.

The ideal candidate is responsible for guiding the development, implementation, and maintenance of complex data solutions in high-risk environments. The role collaborates with cross-functional teams, engages with infrastructure teams, and leads discussions with customers to gather data requirements. The role provides expert guidance on data engineering principles, shapes data architecture, and contributes innovative concepts for information management. The role also provides mentorship and contributes to operational and strategic plans.

The ideal candidate will have a strong understanding of the end-to-end processes across L1 Orgs and LTC (Lead-to-Cash) Workstreams and will help identify scaling opportunities to maximize the impact of automation projects.

Responsibilities :

• Mines data using modern tools and programming languages.
• Defines and implements models to uncover patterns and predictions creating business value and innovation.
• Works with the business to understand the business domain perspective and assess data requirements, contributing to the development and enhancement of best practices and actively participating in data engineering communities.
• Guides the development, implementation, maintenance, and resolution of critical issues within high-risk and complex data solutions for projects or environments with elevated complexity.
• Engages and collaborates with infrastructure teams to ensure the seamless delivery of data-related infrastructure components, aiming for the integration of data engineering deliverables with other project outcomes.
• Advises the solution development team by offering innovative concepts and solutions pertaining to information management and utilizes data engineering solutioning guidelines and tools for developing complex data solutions.
• Collaborates effectively with cross-functional teams, including program and project managers and architects, to ensure successful project outcomes Represents the data science team for all phases of larger and more-complex development projects.
• Assures accuracy, integrity, and compliance of cleansed data.
• Maintains proficiency within the data science domain by keeping up with technology and trend shifts.
• Provides guidance, training and mentoring to less experienced staff members.
• Shapes the data architecture and integration layers, ensuring alignment with enterprise strategies and architectures, and contributes to the creation and upkeep of the enterprise data models.
• Develops and improves automated reporting and monitoring systems for key performance metrics and statistical process control, while also providing mentorship and guidance to lower-level employees.

Education and Skills Required:

• Four-year or Graduate Degree in Computer Science, Information Systems, Engineering, Statistics/ Mathematics, Machine Learning, Data Analytics, Business Administration, or any other related discipline or commensurate work experience or demonstrated competence.
• Typically has 10+ years of work experience, preferably in analytics, data science, reporting, and services and channel RTMs.
• Data Analytics Certifications

Knowledge & Skills:

• Using statistics, mathematics, algorithms, and programming languages.
• Understanding of how to manage disparate unstructured and structured data in a distributed environment.
• Fluent in structured and unstructured data and modern data transformation methodologies.
• Ability to create models to pull valuable insights from data.
• Create stories and visualizations to describe and communicate data insights.
• Ability to use creativity to spot trends and tease out patterns in large datasets.
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills; mastery in English and local language.
• Ability to effectively communicate data insights to project team and leadership and negotiate options.

Disclaimer

This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management.

Job -

Services

Schedule -

Full time

Shift -

No shift premium (Spain)

Travel -

No

Relocation -

Equal Opportunity Employer (EEO) -

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

If you’d like more information about HP’s EEO Policy or your EEO rights as an applicant under the law, please click here: Equal Employment Opportunity is the Law Equal Employment Opportunity is the Law – Supplement