AVP, Big Data and Machine Learning Solutions ArchitectApply Job ID: R-010398 Date posted: 06/29/2020 Primary Location TX-Austin
We are currently seeking an AVP, Big Data and Machine Learning Solutions Architect for LPL Financial Technology organization. This senior level role will be responsible for architecting, designing and lead ML solution development and deployment across verticals and manage data sciences and advanced analytics initiatives. Build Data and ML PipeLines, data integration/engineering, interacts with Data Scientists, Business Owners of verticals, Business Data Analysts, Data Modelers, Architects, and Application Developers, to design, build and manage large-scale batch and real-time data pipelines utilizing various data analytics processing frameworks in support of Data Science practice.
The position requires building strong technical hands-on-skills and experiences as well as establishing close business relationships across different teams. Working closely with all vertical stakeholders, you will develop and drive long term advance analytics roadmap. You will help steer the strategic AI/ML and technology direction, define target state architecture, technology roadmaps, and mentor others.
A successful candidate must have a demonstrable background with experience in development of high performance, ML models using Sage Maker, large scale distributed computing tasks using Big Data technologies such as Hadoop (platform level), Redshift, SnowFlake, NoSQL and other distributed environment technologies based on the needs of the organization. Responsible for analyzing, designing, programming, debugging, and modifying software enhancements and/or new products used in distributed large scale analytics solutions. Strong visualization skills and Experience with BI tools (ex. Tableau)
Work with development teams and other project leaders/stakeholders to provide technical solutions that enable business capabilities
- Will be Subject Matter Expert (SME) and work closely with all verticals (Enterprise Analytics, Marketing, etc.) to enable large-scale use cases, design ML pipelines.
- Data Science and Data Engineering for Structured and unstructured data, Relational and distributed data models
- Proven ability to design, articulate, and deliver complex, large-scale AI/ML solutions that are scalable, robust, secure, and resilient
- Experience in designing solutions that optimize AI performance through advanced HW and software techniques
- Familiarity with leading commercial and Open Source AI / ML / Data Science platforms.
- Maintains a broad understanding of implementation, integration, and inter-connectivity issues with emerging technologies to define data strategies
- Assist in the decision-making process related to the selection of software architecture solutions
- Implement architectures to handle web-scale data and its organization
- Execute strategies that inform data design and architecture partnering with enterprise standard
- Build robust data pipelines on public Cloud using Airflow, AWS EMR, Glue, Kinesis, Kafka, Lambda or other technologies
- Deep expertise in SQL language, Python, Hadoop ecosystem and/or Spark ecosystem. Strong experience with writing complex programs, implementing architectures, and enabling automation in these environments
- Develop and maintain business reporting, ensuring reliability and performance, delivery of performance management tools (such as control charts and scorecards), readiness and adoption of data w/in the organization
- Consolidate, standardize and control changes to capacity management data and metric definitions, ownership, accountability, and taxonomy to ensure alignment in understanding
- Serve as an evangelist to improve AI/ML analytical capability across the organization
- Work across teams to deliver meaningful reference architectures that outline architecture principles and best practices for technology advancement
- Gain adoption of architecture processes, standards and procedures
Work Experience / Knowledge
- 10+ years of experience in data modeling, data warehousing, and big data architectures using Hadoop /EMR, spark, Redshift, Snowflake, No- SQL Cassandra or similar large scale distributed systems
- 5+ years of experience in a data engineering role to build Highly scalable large data pipelines
- Hands-on experience with the creation and automation of Data pipelines and Machine learning pipelines, model training, testing, and deployment using Airflow, EMR, Glue, etc.
- Cloud / hybrid / On-prem deployment architectures
- CPU/GPU/FPGA-based computation
- Proficient in application/software architecture (Definition, Business Process Modeling, etc.)
- Hands-on experience with leading Data Science platforms, Hands-on Experience with AWS Sage Maker, H20 etc
- Deep expertise in (at least one) SQL language, Python, Hadoop ecosystem and/or Spark ecosystem.
- Strong experience with writing complex programs, implementing architectures, and enabling automation in these environments
- The role will be responsible for providing innovative operational solutions and best practices
- Hands-on experience with a broad range of current deep learning tools (TensorFlow, Spark, Theano, PyTorch, Scikit-learn, Keras, Nvidia Digits) and collaboration environments (e.g., Jupyter notebooks, PyCharm)
- Experience with and ability to create solutions using the following models: Deep Learning, GANs, Autoencoders, Reinforcement Learning, Siamese Networks, Logistic Regression, Linear Regression, Support Vector Machines, Hidden Markov Models, Conditional Random Fields, Latent Dirichlet Allocation
- Advanced knowledge in SQL/Hive, Spark, NoSQL, (Java/Python is a plus
- Strong programming skills and the ability to utilize a variety of software/languages/tools, e.g., Spark, R, Python, Scala, Java, Hive, SQL, SAS, Tableau, etc.
- Experience with microservice development, Docker, Kubernetes
- Develop software to run on cloud-native big data infrastructure built on AWS using Spark, Lambda, S3, and other Cloud-native services
- Designs and develops complex and large-scale data structures and pipelines to organize, collect and standardize data to generate insight
- Robust analytics and reporting skills – hands-on Experience in BI Tools like Tableau, Power BI, Salesforce Einstein
- Experience using GitHub, Bit Bucket, or other code repository solution
- DevOps experience with Cloud Formation, Data, and ML pipeline experience.
About LPL Financial:
LPL Financial is a leader in the retail financial advice market and the nation’s largest independent broker/dealer*. We serve independent financial advisors and financial institutions, providing them with the technology, research, clearing and compliance services, and practice management programs they need to create and grow thriving practices. LPL enables them to provide objective guidance to millions of American families seeking wealth management, retirement planning, financial planning and asset management solutions. LPL and its affiliates have more than 4,200 employees with primary offices in Boston, Charlotte, and San Diego.
*As reported by Financial Planning magazine, June 1996-2019, based on total revenue.
If you join LPL, you will join a culture that believes in delivering a world-class client experience and looks to all employees to contribute to that goal by sharing their creativity, experience, and passion for continuous improvement. As a destination of choice, our top priorities are growth and development, social responsibility, and financial health for our employees.
We offer competitive compensation and industry leading benefits, including a wellness facility with onsite fitness classes, healthy meal choices, and a walk-in clinic. We support employee financial health through a 401k match, ESPP, and employee discounts. Work/life balance is our foundation and is supported through paid holidays, and paid time off (including time to volunteer). We foster a diverse work environment through Employee Resource Groups and diverse strategic partnerships.
Join the LPL team and help us make a difference by turning life’s aspirations into financial realities. Please log in or create an account to apply to this position. Principals only. EOE.
Information on Interviews:
LPL will only communicate with a job applicant directly from an @lpl.com email address and will never conduct an interview online or in a chatroom forum. During an interview, LPL will not request any form of payment from the applicant, or information regarding an applicant’s bank or credit card. Should you have any questions regarding the application process, please contact LPL’s Human Resources Solutions Center at (800) 877-7210.