Senior Data Scientist (AI/ML)

Senior Data Scientist (AI/ML)

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:

What you’ll do:

• Leads as well as develops scalable AI solutions using relevant AI (ML/DL/Gen AI) techniques
• Architects large scale AI solutions that seamlessly merge AI model and techniques in SDLC
• Organizes and leads comprehensive code and design review sessions, driving discussions to align with project requirements and best practices. Mentor and provide feedback to junior and mid-level team members.
• Conducts research and stays up to date with the latest advancements in AI and machine learning technologies, frameworks, and algorithms. Explore and experiment with cutting-edge techniques to solve complex problems and improve existing models.
• Collaborates with cross-functional teams to understand business requirements and design AI and machine learning solutions. Determine the appropriate algorithms, models, and frameworks to use and architect the overall system to ensure scalability, efficiency, and robustness.
• Develops, implements, and optimizes machine learning models and algorithms. This includes data pre-processing, feature engineering, model selection, hyperparameter tuning, and training on large datasets. Continuously monitor and improve model performance and accuracy.
• Leverage or build analytics tools that utilize the data pipeline to provide significant insights into customer case data, bug data, operational and other key business performance metrics.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
• Work with data and analytics specialists to strive for greater functionality in our data systems.
• Identify trends, patterns from dataset to scope opportunities for automation
• Deploys machine learning models into production environments, considering scalability, performance, and security considerations.
• Integrate models with existing software systems and infrastructure, ensuring smooth operation and interoperability.
• Monitors the performance of deployed models, collects relevant metrics, and analyzes data to identify areas for improvement. Based on insights gained from monitoring and analysis, fine-tune models, optimize algorithms, and enhance system performance.
• Works collaboratively with the engineering manager and team lead to set design and implementation standards, ensuring continuous improvement and alignment with project goals.
• Regularly leads meetings, fostering a collaborative and productive team environment.
• Has experience in providing technical leadership, mentorship, and guidance to junior team members.
• Address and resolve challenges proactively.
• Develops and delivers strategic presentations and reports to senior stakeholders, demonstrating a deep understanding of technical and business aspects. Provide insights and recommendations.
• Applies and leverages data mining, data modeling, natural language processing, and machine learning to extract and analyze information from datasets.

What you need to bring:

• We are looking for a candidate with 9+ years of experience in a Data science role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
• 5+ years experience building data pipelines for data science-driven solutions and deployed in Production environment
• Experience working in technical support environment, working with dataset from CRM, H/W and S/W bugs data, machine logs
• Experience supporting and working with multi-functional teams in a multidimensional fast paced environment.
• Good team worker with excellent interpersonal, written, verbal and presentation skills
• Experience building and optimizing data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and find opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large, disconnected datasets.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Strong hands-on coding skills (preferably in Python) processing large-scale data set and developing machine learning model
• A strong foundation in mathematics and statistics. In-depth knowledge of linear algebra, calculus, probability theory, and statistical concepts. Understanding and developing complex machine learning models and algorithms.
• Good knowledge on Software Development Life Cycle and Agile principles
• Experience working with Large Language models, Generative AI, Conversational AI
• Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow, NLP libraries
• Experience working with Databricks, Snowflake platforms
• Experience with AWS, S3, Spark, Kafka, Elastic Search
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.

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.

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Job:

Engineering

Job Level:

TCP_04

    

    

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.