Director of Analytics and Machine Learning strategy

HP   •  

Houston, TX

5 - 7 years

Posted 238 days ago

This job is no longer available.

Are you someone interested in working in an agile start-up environment while leveraging the brand recognition, solution capabilities and global reach of one of the world’s largest IT corporations?  The Emerging Compute Solutions team operates in a highly dynamic landscape with a product portfolio that encompasses commercial services, analytics and machine learning, commercial mobility devices, retail point of sale devices, thin clients and workflow transformation.  The business unit is looking to build and develop a best-in-class, multi-OS Services portfolio powered by software, cloud, analytics and machine learning as well as expert IT resources.   Our services portfolio will power HP’s Device as a Service (DaaS). 

HP is staffing a director level, product manager position to lead our Analytics and Machine Learning strategy across hardware, software and services.  The Director of Data Science and Machine Learning, will drive data-driven answers to complex strategic challenges.  Specifically, this person is responsible for the roadmap and competitive leadership of the product portfolio and overall adoption and success of our Device as a Service (DaaS) portfolio where we are using analytics and machine learning as differentiators.  This role is focused on defining our analytics strategy for HPI, for creating quantitative strategies across hardware, software, apps and contextual usage as well as developing external quantitative related business development and partnership opportunities. This role will develop products that differentiate our hardware portfolio as well as create intelligent services that solve customer pain points.  This position reports to the VP and Head of Services & Software Product Management in the Emerging Compute Solutions global business unit.  This position will be based out of Houston, Texas.

Responsibilities & Qualifications:

  • Ability to develop a long-term vision for HP’s software and services solutions
  • Influence hardware, software and cloud product development to deliver innovative analytics and machine learning capabilities for our portfolio
  • Influence Go-to-market: develop go-to-market strategy and ensure execution in partnership with the sales, channel and marketing teams in HP
  • Direct and influence multiple groups across diverse business units to drive unified solutions
  • VP-level strategic and tactical engagement both internally and with external partners
  • Identify and prioritize key ecosystem partners and drive technical and business alignment with our product/ services offerings by leveraging our partner ecosystem
  • Partner with hardware development groups to develop integrated software/cloud/hardware solutions
  • Enable a feature set that resonates with service providers, our channel partners and Web 2.0 businesses, relating product capabilities in terms that they understand, care about, and are willing to pay for.
  • Influence the engineering product development of cloud-based IT (including IT infrastructure, connectivity and applications) solutions
  • Assess customer insights and market trends and inflection points to determine the right bets for HP
  • Maintain industry and customer segment relationships and serve as internal customer segment or industry expert.

Daily work will involve performing one or more of the following activities:

  • Translating a complex strategic challenge into relevant analytic framework(s):
  • Setup and lead meetings to gather business requirements using interviews and questionnaire.
  • Ask probing questions to understand business intent and how the end-results will be used. Surface implicit assumptions by the business user. Agree on template end-deliverables.
  • Perform due diligence to ensure data is obtainable for the analysis required, and the analysis can be completed in the timeline requested.

Gathering, cleaning and structuring existing data:

  • Identify relevant data sources (from data warehouses, CRM, ERP, web logs, business intelligence, partner data sources, research reports, surveys, and interviews).
  • Determine appropriate analytic approach (e.g. skim relevant data or creation of structured database for manipulation, etc.)
  • Where required, pull data into analytic environment using Oracle, SQL, Hadoop, Access or Excel.
  • Where relevant, clean and structure data to facilitate analysis and guide engineering.
  • Identify and catalog strengths and weakness of respective data sources, noting areas of questionable data that could sidetrack analytic output.

Formulating hypotheses for testing and designing experiments to capture new data:

  • Identify practical approach to test and learn key hypotheses to extend analytic insight.
  • Design, implement and manage new approaches for data capture/databases.
  • Leverage new data and/or experiment results to extend analytic frameworks/algorithms.

Applying appropriate decision technology tools, algorithms and methodologies:

  • Identify appropriate decision technology techniques to apply to relevant analytic frameworks.  Examples of decision technology tools that may be used include optimization, simulation, regression, decision trees, neural networks, cluster analysis, mixed models, etc. 
  • Set up model and conduct analyses using tools using Excel and SPSS.  Additional tools may include MatLab, MapReduce, JMP, SAP BI, IBM Cognos, R, SAS, Minitab.
  • Write  or direct custom code as required.
  • This position does require an individual who has experience and knowledge of how to learn and apply data science techniques and tools.   
  • Document steps, data sources. Ensure models are easily understandable and maintainable.

Distilling and presenting analytic results to a non-technical audience:

  • Create and deliver executive level presentations.

Professional Experience/Qualifications:

  • A rigorous understanding of the fundamentals of statistics applied to business challenges and microeconomics is required
  • 5+ years of experience in data analysis, business development or corporate strategy with heavy emphasis on data-driven decision making is required.
  • A strong curiosity to learn and apply data science techniques and tools is required.
  • Strong undergraduate and/or graduate degree in STEM disciplines (Science, Technology, Engineering, Math) or in other disciplines with heavy focus on statistics.  Quantitative-oriented MBA desired. 
  • Familiarity with decision techniques including optimization, simulation, regression, decision trees, neural networks, cluster analysis, mixed models, is preferred. 
  • Proven ability to work within a climate of ambiguity.
  • Outstanding communication and presentation skills a must.
  • Strong business acumen; sound business-sense and judgment.
  • Demonstrated leadership competencies such as teamwork, creative problem solving, flexibility and willingness to challenge the status quo.
  • Excellent relationship management, strong team building, and the ability to work across business units and functions within complex organizations.
  • Excellent interpersonal skills and negotiation skills is desired. 
  • Deep knowledge of cloud services, software and PC hardware technology
  • Excellent written/oral communications and analytical skills
  • Excellent interpersonal skills; ability to build, manage and influence virtual teams
  • Excellent negotiating skills
  • Ability to interface effectively with all levels of management and functional disciplines
  • Excellent influencing, consensus-building and conflict-resolution skills
  • Quantifiable and tangible track record of developing and delivering products and solutions across cross-functional matrices in a Fortune 500 technology company
  • Prior experience to develop and take new initiatives to launch

Job ID 3021011