Principle Data Scientist

Principle Data Scientist

  

This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week from an HPE office.

Job Description:

   

cience

Job Family Definition:

Designs, develops and applies programs, methodologies and systems based on advanced analytic models (e.g. advanced statistics, operations research, computer science, process) to transform structured and unstructured data into meaningful and actionable information insights that drive decision making.

Uses visualization techniques to translate analytic insights into understandable business stories (eg. descriptive, inferential and predictive insights).

Embeds analytics into client’s business processes and applications. Combines business acumen and scientific methods to solve business problems.

Management Level Definition:

Contributions have visible technical impact on a product or major subcomponent.  Applies in-depth professional knowledge and innovative ideas to solve complex problems. Visible contributions improve time-to-market, achieve cost reductions, or satisfy current and future unmet customer needs. Recognized internal authority on key technology area applying innovative principles and ideas. Provides technical leadership for significant project/program work. Leads or participates in cross-functional initiatives and contributes to mentorship and knowledge sharing across the organization.

What you'll do:

Responsibilities:

• Defines and develops the value proposition to lead the formulation and definition of analytics solution objectives and technical requirements based on user needs, an understanding of business value industry requirements and advanced analytic models (statistical, operations research, computing, process).
• Conceptualizes, builds, develops, and enhances a client's analytic model.  Determines the right modeling methodology for the use case, available structured and unstructured data, cost and timing constraints to solve the large and complex business issues and delivers compelling and clear business focused insights.
• Design and engineer Machine Learning solutions.
• Can work with multiple databases and big data solutions.
• Standardize ELT, BI, governance, and analytics.
• Technically lead, Design, and develop distributed, high-throughput, low-latency, highly available solutions.
• Understand business requirement to build reliable data infrastructure using big data technologies.
• Work with the data engineering team to develop & maintain data pipelines for batch & stream processing.
• Identify, design, and implement internal process improvements and tools to automate data processing and ensure data integrity while meeting data security standards
• Build tools for better discovery and consumption of data for various consumption models in the organization – DataMarts, Warehouses, APIs, Adhoc Data explorations
• Create data views from big data store to feed into analysis engines, visualization engines etc.
• Work with data scientist and business analytics team to assist in data ingestion and data-related technical issues.
• Drive top-line growth and profitability across our eCommerce by turning transaction-level data into actionable pricing, assortment, and acquisition strategies that improve GM, FM, and contribution margins.
• Build and maintain forecasting models (hierarchical/time-series, causal models) for SKU-, category- and channel-level demand, revenue and inventory planning
• Build Model / ranking algorithms to identify customer behavior patterns using transactional and customer journey data.

What you need to bring:

Education and Experience Required:

• PhD degree in Statistics, Operations Research, Computer Science or equivalent and 8+ years of relevant experience. Or Master´s Degree in these areas and at least 8 years of relevant experience.

Knowledge and Skills:

• Extensive knowledge of data science methodologies including but not limited to classical regression, neural nets, CHAID, CART, association rules, sequence analysis, cluster analysis, and text mining.
• Extensive understanding of analytics software (eg. R,  Python, RapidMiner).  Advanced understanding of analytics deployment architectures.
• Ability to translate business requirements into mathematical models and data science objectives to achieve measurable business outcomes.
• Ability to build and implement models in data bricks
• Experience working with Google Analytics, Adobe Analytics, or similar platforms.
• Analyze financial data to identify trends, variances, and opportunities for improvement
• Familiarity with FP&A (Financial Planning & Analysis) processes
• Expert SQL
• Expert ETL/ELT
• Relational Databases
• Ability to create solutions utilizing big data environments (Hadoop, Kafka, Hive, spark)
• Data warehousing
• Data Modeling
• Python
• Qlik
• Power BI

#DataScience

Accountability, Accountability, Action Planning, Active Learning, Active Listening, Agile Methodology, Agile Scrum Development, Analytical Thinking, Bias, Coaching, Creativity, Critical Thinking, Cross-Functional Teamwork, Data Analysis Management, Data Collection Management (Inactive), Data Controls, Design, Design Thinking, Empathy, Follow-Through, Group Problem Solving, Growth Mindset, Intellectual Curiosity (Inactive), Long Term Planning, Managing Ambiguity {+ 5 more}

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

#india

Job:

Engineering

Job Level:

TCP_05

    

    

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

   

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

   

No Fees Notice & Recruitment Fraud Disclaimer

 

It has come to HPE’s attention that there has been an increase in recruitment fraud whereby scammer impersonate HPE or HPE-authorized recruiting agencies and offer fake employment opportunities to candidates.  These scammers often seek to obtain personal information or money from candidates.

 

Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge any candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process.  The credentials of any hiring agency that claims to be working with HPE for recruitment of talent should be verified by candidates and candidates shall be solely responsible to conduct such verification. Any candidate/individual who relies on the erroneous representations made by fraudulent employment agencies does so at their own risk, and HPE disclaims liability for any damages or claims that may result from any such communication.