NLP Engineer - Artificial Intelligence

Please note - This is a 100% remote opportunity and you can work from any location.

 

About the team:

You will be a part of Cactus Labs which is the R&D Cell of Cactus Communications. Cactus Labs is a high impact cell that works to solve complex technical and business problems that help keep us strategically competitive in the industry. We are a multi-cultural team spread across multiple countries. We work in the domain of AI/ML especially with Text (NLP - Natural Language Processing), Language Understanding, Explainable AI, Big Data, AR/VR etc.

 

The opportunity: Within Cactus Labs you will work with the Big Data team. This team manages Terabytes of data coming from different sources. We are re-orchestrating data pipelines to handle this data at scale and improve visibility and robustness. We operate across all the three Cloud Platforms and leverage the best of them.

 

In this role, you will get to own a component end to end. You will also get to work on cloud platform and learn to design distributed data processing systems to operate at scale.

 

Responsibilities:

• Collaborate with a team of Big Data Engineers, Big Data and Cloud Architects and Domain SMEs to drive the product ahead
• Stay up to date with the progress of in the domain since We work on cutting-edge technologies and are constantly trying new things out
• Build solutions for massive scale. This requires extensive benchmarking to pick the right approach
• Understand the data in and out, and make sense of it. You will at times need to draw conclusions and present it to the business users
• Be independent, self-driven and highly motivated. While you will have the best people to learn from and access to various courses or training materials, we expect you to take charge of your growth and learning.

 

Expectations from you:

• 1-3 Year of relevant experience in Big Data with pySpark
• Hands on experience of distributed computing and Big Data Ecosystem - Hadoop, HDFS, Spark etc
• Good understanding of data lake and their importance in a Big Data Ecosystem
• Experience of working in the Cloud Environment (AWS, Azure or GCP)
• You like to work without a lot of supervision or micromanagement.
• Above all, you get excited by data. You like to dive deep, mine patterns and draw conclusions. You believe in making data driven decisions and helping the team look for the pattern as well.

 

Preferred skills:

• Familiarity with search engines like Elasticsearch and Bigdata warehouses systems like AWS Athena, Google Big Query etc
• Building data pipelines using Airflow
• Experience of working in AWS Cloud Environment
• Knowledge of NLP and ML

Responsibilities

● Able contribute to the gathering of functional requirements, developing technical
specifications, and project & test planning
● Demonstrating technical expertise, and solving challenging programming and design
problems
● Roughly 80% hands-on coding
● Generate technical documentation and PowerPoint presentations to communicate
architectural and design options, and educate development teams and business users
● Resolve defects/bugs during QA testing, pre-production, production, and post-release
patches
● Work cross-functionally with various bidgely teams including: product management,
QA/QE, various product lines, and/or business units to drive forward results

Requirements
● BS/MS in computer science or equivalent work experience
● 2-4 years’ experience designing and developing applications in Data Engineering
● Hands-on experience with Big data Eco Systems.
● Hadoop,Hdfs,Map Reduce,YARN,AWS Cloud, EMR, S3, Spark, Cassandra, Kafka,
Zookeeper
● Expertise with any of the following Object-Oriented Languages (OOD): Java/J2EE,Scala,
Python
● Strong leadership experience: Leading meetings, presenting if required
● Excellent communication skills: Demonstrated ability to explain complex technical
issues to both technical and non-technical audiences
● Expertise in the Software design/architecture process
● Expertise with unit testing & Test-Driven Development (TDD)
● Experience on Cloud or AWS is preferable
● Have a good understanding and ability to develop software, prototypes, or proofs of
concepts (POC's) for various Data Engineering requirements.

Roles and Responsibilities:

• Responsible for developing and maintaining applications with PySpark 

Technical Knowledge (Must Have)

• Strong experience in SQL / HiveQL/ AWS Athena,
• Strong expertise in the development of data pipelines (snaplogic is preferred).
• Design, Development, Deployment and administration of data processing applications.
• Good Exposure towards AWS and Azure Cloud computing environments.
• Knowledge around BigData, AWS Cloud Architecture, Best practices, Securities, Governance, Metadata Management, Data Quality etc.
• Data extraction through various firm sources (RDBMS, Unstructured Data Sources) and load to datalake with all best practices.
• Knowledge in Python
• Good knowledge in NoSQL technologies (Neo4J/ MongoDB)
• Experience/knowledge in SnapLogic (ETL Technologies)
• Working knowledge on Unix (AIX, Linux), shell scripting
• Experience/knowledge in Data Modeling. Database Development
• Experience/knowledge creation of reports and dashboards in Tableau/ PowerBI

The Director for Data Science will support building of AI products in Agile fashion that
empower healthcare payers, providers and members to quickly process medical data to
make informed decisions and reduce health care costs. You will be focusing on research,
development, strategy, operations, people management, and being a thought leader for
team members based out of India. You should have professional healthcare experience
using both structured and unstructured data to build applications. These applications
include but are not limited to machine learning, artificial intelligence, optical character
recognition, natural language processing, and integrating processes into the overall AI
pipeline to mine healthcare and medical information with high recall and other relevant
metrics. The results will be used dually for real-time operational processes with both
automated and human-based decision making as well as contribute to reducing
healthcare administrative costs. We work with all major cloud and big data vendors
offerings including (Azure, AWS, Google, IBM, etc.) to achieve our goals in healthcare and
support 
The Director, Data Science will have the opportunity to build a team, shape team culture
and operating norms as a result of the fast-paced nature of a new, high-growth
organization.

• Strong communication and presentation skills to convey progress to a diverse group of stakeholders
• Strong expertise in data science, data engineering, software engineering, cloud vendors, big data technologies, real-time streaming applications, DevOps and product delivery
• Experience building stakeholder trust and confidence in deployed models especially via application of the algorithmic bias, interpretable machine learning,
data integrity, data quality, reproducible research and reliable engineering 24x7x365 product availability, scalability
• Expertise in healthcare privacy, federated learning, continuous integration and deployment, DevOps support
• Provide mentoring to data scientists and machine learning engineers as well as career development
• Meet project related team members for individual specific needs on a regular basis related to project/product deliverables
• Provide training and guidance for team members when required
• Provide performance feedback when required by leadership

The Experience You’ll Need (Required):
• MS/M.Tech degree or PhD in Computer Science, Mathematics, Physics or related STEM fields
• Significant healthcare data experience including but not limited to usage of claims data
• Delivered multiple data science and machine learning projects over 8+ years with values exceeding $10 Million or more and has worked on platform members exceeding 10 million lives
• 9+ years of industry experience in data science, machine learning, and artificial intelligence
• Strong expertise in data science, data engineering, software engineering, cloud vendors, big data technologies, real time streaming applications, DevOps, and product delivery
• Knows how to solve and launch real artificial intelligence and data science related problems and products along with managing and coordinating the
business process change, IT / cloud operations, meeting production level code standards
• Ownerships of key workflows part of data science life cycle like data acquisition, data quality, and results
• Experience building stakeholder trust and confidence in deployed models especially via application of algorithmic bias, interpretable machine learning,
data integrity, data quality, reproducible research, and reliable engineering 24x7x365 product availability, scalability
• Expertise in healthcare privacy, federated learning, continuous integration and deployment, DevOps support
• 3+ Years of experience managing directly five (5) or more senior level data scientists, machine learning engineers with advanced degrees and directly
made staff decisions

• Very strong understanding of mathematical concepts including but not limited to linear algebra, advanced calculus, partial differential equations, and
statistics including Bayesian approaches at master’s degree level and above
• 6+ years of programming experience in C++ or Java or Scala and data science programming languages like Python and R including strong understanding of
concepts like data structures, algorithms, compression techniques, high performance computing, distributed computing, and various computer architecture
• Very strong understanding and experience with traditional data science approaches like sampling techniques, feature engineering, classification, and
regressions, SVM, trees, model evaluations with several projects over 3+ years
• Very strong understanding and experience in Natural Language Processing,
reasoning, and understanding, information retrieval, text mining, search, with
3+ years of hands on experience
• Experience with developing and deploying several products in production with
experience in two or more of the following languages (Python, C++, Java, Scala)
• Strong Unix/Linux background and experience with at least one of the
following cloud vendors like AWS, Azure, and Google
• Three plus (3+) years hands on experience with MapR \ Cloudera \ Databricks
Big Data platform with Spark, Hive, Kafka etc.
• Three plus (3+) years of experience with high-performance computing like
Dask, CUDA distributed GPU, TPU etc.
• Presented at major conferences and/or published materials

Simplilearn.com is the world’s largest professional certifications company and an Onalytica Top 20 influential brand. With a library of 400+ courses, we've helped 500,000+ professionals advance their careers, delivering $5 billion in pay raises. Simplilearn has over 6500 employees worldwide and our customers include Fortune 1000 companies, top universities, leading agencies and hundreds of thousands of working professionals. We are growing over 200% year on year and having fun doing it. Description We are looking for candidates with strong technical skills and proven track record in building predictive solutions for enterprises. This is a very challenging role and provides an opportunity to work on developing insights based Ed-Tech software products used by large set of customers across globe. It provides an exciting opportunity to work across various advanced analytics & data science problem statement using cutting-edge modern technologies collaborating with product, marketing & sales teams. Responsibilities • Work on enterprise level advanced reporting requirements & data analysis. • Solve various data science problems customer engagement, dynamic pricing, lead scoring, NPS improvement, optimization, chatbots etc. • Work on data engineering problems utilizing our tech stack - S3 Datalake, Spark, Redshift, Presto, Druid, Airflow etc. • Collect relevant data from source systems/Use crawling and parsing infrastructure to put together data sets. • Craft, conduct and analyse A/B experiments to evaluate machine learning models/algorithms. • Communicate findings and take algorithms/models to production with ownership. Desired Skills • BE/BTech/MSc/MS in Computer Science or related technical field. • 2-5 years of experience in advanced analytics discipline with solid data engineering & visualization skills. • Strong SQL skills and BI skills using Tableau & ability to perform various complex analytics in data. • Ability to propose hypothesis and design experiments in the context of specific problems using statistics & ML algorithms. • Good overlap with Modern Data processing framework such as AWS-lambda, Spark using Scala or Python. • Dedication and diligence in understanding the application domain, collecting/cleaning data and conducting various A/B experiments. • Bachelor Degree in Statistics or, prior experience with Ed-Tech is a plus

REQUIREMENT:

•  Previous experience of working in large scale data engineering
•  4+ years of experience working in data engineering and/or backend technologies with cloud experience (any) is mandatory.
•  Previous experience of architecting and designing backend for large scale data processing.
•  Familiarity and experience of working in different technologies related to data engineering – different database technologies, Hadoop, spark, storm, hive etc.
•  Hands-on and have the ability to contribute a key portion of data engineering backend.
•  Self-inspired and motivated to drive for exceptional results.
•  Familiarity and experience working with different stages of data engineering – data acquisition, data refining, large scale data processing, efficient data storage for business analysis.
•  Familiarity and experience working with different DB technologies and how to scale them.

RESPONSIBILITY:

•  End to end responsibility to come up with data engineering architecture, design, development and then implementation of it.
•  Build data engineering workflow for large scale data processing.
•  Discover opportunities in data acquisition.
•  Bring industry best practices for data engineering workflow.
•  Develop data set processes for data modelling, mining and production.
•  Take additional tech responsibilities for driving an initiative to completion
•  Recommend ways to improve data reliability, efficiency and quality
•  Goes out of their way to reduce complexity.
•  Humble and outgoing - engineering cheerleaders.

RESPONSIBILITIES AND QUALIFICATIONS The mission of the Marcus Surveillance Analytics team is to deliver a platform which detects security incidents which have a tangible business impact and actionable response. You will work alongside industry leading technologists from who have recently joined Goldman from across consumer security, technology, fintech, finance and quant firms. The role has a broad scope which will involve interacting with senior leaders of Goldman and the Consumer business on a regular basis. The position is hands-on and requires a driven and “take ownership” oriented individual who is intently focused on execution. You will work directly with developers, business leaders, vendors and partners in order to deliver security assets to the consumer business. Develop a team, vision and platform which identifies/prioritizes actionable security & fraud risks which have tangible businesses impact across Goldman's consumer and commercial banking businesses. Develop response and recovery technology and programs to ensure resilience from fraud and abuse events. Manage, develop and operationalize analytics which discover security & fraud events and identifies risks for all of Goldman's consumer businesses. Partner with fraud / abuse operations and leadership to ensure consumer fraud rates are within industry norms and own outcomes related to fraud improvements. Skills And Experience We Are Looking For BA/BS degree in Computer Science, Cybersecurity, or other relevant Computer/Data/Engineering degrees 2+ years of experience as a security professional or data analyst/scientist/engineer Python, PySpark, R, Bash, SQL, Splunk (search, ES, UBA) Experience with cloud infrastructure/big data tool sets Visualization tools such as Tableau or D3 Research and development to create innovative predictive detections for security and fraud Build a 24/7 real-time monitoring system with long term vision for scaling to new lines of consumer businesses Strong focus on customer experience and product usability Ability to work closely with the business, fraud, and security incident response teams on creating actionable detections