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
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Required skills and experience: · Solid experience working in Big Data ETL environments with Spark and Java/Scala/Python · Strong experience with AWS cloud technologies (EC2, EMR, S3, Kinesis, etc) · Experience building monitoring/alerting frameworks with tools like Newrelic and escalations with slack/email/dashboard integrations, etc · Executive-level communication, prioritization, and team leadership skills
Machine Learning Engineer
at Contact Center software that leverages AI to improve custome
As a machine learning engineer on the team, you will
• Help science and product teams innovate in developing and improving end-to-end
solutions to machine learning-based security/privacy control
• Partner with scientists to brainstorm and create new ways to collect/curate data
• Design and build infrastructure critical to solving problems in privacy-preserving machine
learning
• Help team self-organize and follow machine learning best practice.
Basic Qualifications
• 4+ years of experience contributing to the architecture and design (architecture, design
patterns, reliability and scaling) of new and current systems
• 4+ years of programming experience with at least one modern language such as Java,
C++, or C# including object-oriented design
• 4+ years of professional software development experience
• 4+ years of experience as a mentor, tech lead OR leading an engineering team
• 4+ years of professional software development experience in Big Data and Machine
Learning Fields
• Knowledge of common ML frameworks such as Tensorflow, PyTorch
• Experience with cloud provider Machine Learning tools such as AWS SageMaker
• Programming experience with at least two modern language such as Python, Java, C++,
or C# including object-oriented design
• 3+ years of experience contributing to the architecture and design (architecture, design
patterns, reliability and scaling) of new and current systems
• Experience in python
• BS in Computer Science or equivalent
Machine Learning Engineer - NLP
at Leena AI
Responsibilities:
- Improve robustness of Leena AI current NLP stack
- Increase zero shot learning capability of Leena AI current NLP stack
- Opportunity to add/build new NLP architectures based on requirements
- Manage End to End lifecycle of the data in the system till it achieves more than 90% accuracy
- Manage a NLP team
Page BreakRequirements:
- Strong understanding of linear algebra, optimisation, probability, statistics
- Experience in the data science methodology from exploratory data analysis, feature engineering, model selection, deployment of the model at scale and model evaluation
- Experience in deploying NLP architectures in production
- Understanding of latest NLP architectures like transformers is good to have
- Experience in adversarial attacks/robustness of DNN is good to have
- Experience with Python Web Framework (Django), Analytics and Machine Learning frameworks like Tensorflow/Keras/Pytorch.
Azure – Data Engineer
- At least 2 years hands on experience working with an Agile data engineering team working on big data pipelines using Azure in a commercial environment.
- Dealing with senior stakeholders/leadership
- Understanding of Azure data security and encryption best practices. [ADFS/ACLs]
Data Bricks –experience writing in and using data bricks Using Python to transform, manipulate data.
Data Factory – experience using data factory in an enterprise solution to build data pipelines. Experience calling rest APIs.
Synapse/data warehouse – experience using synapse/data warehouse to present data securely and to build & manage data models.
Microsoft SQL server – We’d expect the candidate to have come from a SQL/Data background and progressed into Azure
PowerBI – Experience with this is preferred
Additionally
- Experience using GIT as a source control system
- Understanding of DevOps concepts and application
- Understanding of Azure Cloud costs/management and running platforms efficiently
Primary Skills
6 to 8 years of relevant work experience in ETL tools
Good knowledge working in AWS Cloud Data Bases like Aurora DB and ecosystem and tools (AWS DMS)
Migrating databases to AWS Cloud would be Mandatory
Sound knowledge of SQL and procedural language.
Possess solid experience of writing complex SQL queries and optimizing SQL query performance
Knowledge of data ingestion one-off feed, change data capture, incremental batch
Additional Skills :
Experience in Unix/Linux systems and writing shell scripts would be nice to have
Java knowledge would be an added advantage
Knowledge in Spark Python for building ETL pipelines on cloud would be preferable
This is NOT remote work position and the selected candidate is expected to commute to the office location in Navi Mumbai.
Job Description
- Implement and deliver a product in the healthcare domain using machine learning and AI capabilities
- Ability to work on challenging tasks
- Ability to research ways of doing things efficiently
- Keen approach to problem solving
- Strong experience in statistics, python, SQL, NLP and predictiv modeling
Basic Qualifications
- Bachelors Degree with a total of 9+ years of experience in software development with 2-3 years experience in Data Science
- Experienced in working with large and multiple datasets, data warehouses and ability to pull data using relevant programs and coding
- Well versed with necessary data preprocessing and feature engineering skills
- Background in healthcare IT space will be preferred
Understand various raw data input formats, build consumers on Kafka/ksqldb for them and ingest large amounts of raw data into Flink and Spark.
Conduct complex data analysis and report on results.
Build various aggregation streams for data and convert raw data into various logical processing streams.
Build algorithms to integrate multiple sources of data and create a unified data model from all the sources.
Build a unified data model on both SQL and NO-SQL databases to act as data sink.
Communicate the designs effectively with the fullstack engineering team for development.
Explore machine learning models that can be fitted on top of the data pipelines.
Mandatory Qualifications Skills:
Deep knowledge of Scala and Java programming languages is mandatory
Strong background in streaming data frameworks (Apache Flink, Apache Spark) is mandatory
Good understanding and hands on skills on streaming messaging platforms such as Kafka
Familiarity with R, C and Python is an asset
Analytical mind and business acumen with strong math skills (e.g. statistics, algebra)
Problem-solving aptitude
Excellent communication and presentation skills
Key Responsibilities:
- Partnering with clients and internal business owners (product, marketing, edit, etc.) to understand needs and develop models and products for Kaleidofin business line.
- Good understanding of the underlying business and workings of cross functional teams for successful execution
- Design and develop analyses based on business requirement needs and challenges.
- Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, hyperparameter tuning, ensembling etc.
- Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
- Identify and use appropriate investigative and analytical technologies to interpret and verify results.
- Apply and learn a wide variety of tools and languages to achieve results
- Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.
- Collaborate with the team to improve the effectiveness of business decisions using data and machine learning/predictive modeling.
- Innovate on projects by using new modeling techniques or tools.
- Utilize effective project planning techniques to break down complex projects into tasks and ensure deadlines are kept.
- Communicate findings to team and leadership to ensure models are well understood and incorporated into business processes.
Skills:
- 2+ year experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
- Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, Boosting trees, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, ensemble methods.
- Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools
- Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
- Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
- Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE)
- Experience in risk and credit scoring domains preferred
data domain.
● Should have experience in architecting data ecosystem for streaming data and
analytical platforms.
● Expert level experience in building fault-tolerant & scalable big-data platforms and
big-data solutions primarily based on the Hadoop ecosystem.
● Expert level experience with Java, Python or Scala programming.
● Expert level experience designing high throughput data services.
● Familiarity with machine learning and AI.
● Experience with Big-Data Technologies (Hive, HBase, Spark, Kafka, Storm,
MapReduce, HDFS, Zookeeper, Scylla, Cassandra, Yarn), understands the
concepts and technology ecosystem around both real-time and batch processing in
Hadoop.
● Strong spoken and written communication skills.
● B.E/B.Tech/MS in Computer Science (or equivalent).
● Effective listening skills and strong collaboration
Data Engineer
at Pluto Seven Business Solutions Pvt Ltd