• Responsible for developing and maintaining applications with PySpark
Must Have Skills:
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ABOUT EPISOURCE:
Episource has devoted more than a decade in building solutions for risk adjustment to measure healthcare outcomes. As one of the leading companies in healthcare, we have helped numerous clients optimize their medical records, data, analytics to enable better documentation of care for patients with chronic diseases.
The backbone of our consistent success has been our obsession with data and technology. At Episource, all of our strategic initiatives start with the question - how can data be “deployed”? Our analytics platforms and datalakes ingest huge quantities of data daily, to help our clients deliver services. We have also built our own machine learning and NLP platform to infuse added productivity and efficiency into our workflow. Combined, these build a foundation of tools and practices used by quantitative staff across the company.
What’s our poison you ask? We work with most of the popular frameworks and technologies like Spark, Airflow, Ansible, Terraform, Docker, ELK. For machine learning and NLP, we are big fans of keras, spacy, scikit-learn, pandas and numpy. AWS and serverless platforms help us stitch these together to stay ahead of the curve.
ABOUT THE ROLE:
We’re looking to hire someone to help scale Machine Learning and NLP efforts at Episource. You’ll work with the team that develops the models powering Episource’s product focused on NLP driven medical coding. Some of the problems include improving our ICD code recommendations, clinical named entity recognition, improving patient health, clinical suspecting and information extraction from clinical notes.
This is a role for highly technical data engineers who combine outstanding oral and written communication skills, and the ability to code up prototypes and productionalize using a large range of tools, algorithms, and languages. Most importantly they need to have the ability to autonomously plan and organize their work assignments based on high-level team goals.
You will be responsible for setting an agenda to develop and ship data-driven architectures that positively impact the business, working with partners across the company including operations and engineering. You will use research results to shape strategy for the company and help build a foundation of tools and practices used by quantitative staff across the company.
During the course of a typical day with our team, expect to work on one or more projects around the following;
1. Create and maintain optimal data pipeline architectures for ML
2. Develop a strong API ecosystem for ML pipelines
3. Building CI/CD pipelines for ML deployments using Github Actions, Travis, Terraform and Ansible
4. Responsible to design and develop distributed, high volume, high-velocity multi-threaded event processing systems
5. Knowledge of software engineering best practices across the development lifecycle, coding standards, code reviews, source management, build processes, testing, and operations
6. Deploying data pipelines in production using Infrastructure-as-a-Code platforms
7. Designing scalable implementations of the models developed by our Data Science teams
8. Big data and distributed ML with PySpark on AWS EMR, and more!
BASIC REQUIREMENTS
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Bachelor’s degree or greater in Computer Science, IT or related fields
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Minimum of 5 years of experience in cloud, DevOps, MLOps & data projects
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Strong experience with bash scripting, unix environments and building scalable/distributed systems
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Experience with automation/configuration management using Ansible, Terraform, or equivalent
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Very strong experience with AWS and Python
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Experience building CI/CD systems
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Experience with containerization technologies like Docker, Kubernetes, ECS, EKS or equivalent
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Ability to build and manage application and performance monitoring processes
Requirements-
● B.Tech/Masters in Mathematics, Statistics, Computer Science or another quantitative field
● 2-3+ years of work experience in ML domain ( 2-5 years experience )
● Hands-on coding experience in Python
● Experience in machine learning techniques such as Regression, Classification,Predictive modeling, Clustering, Deep Learning stack, NLP.
● Working knowledge of Tensorflow/PyTorch
Optional Add-ons-
● Experience with distributed computing frameworks: Map/Reduce, Hadoop, Spark etc.
● Experience with databases: MongoDB
About Us:
Cognitio Analytics is an award-winning, niche service provider that offers digital transformation solutions powered by AI and machine learning. We help clients realize the full potential of their data assets and the investments made in related technologies, be it analytics and big data platforms, digital technologies or your people. Our solutions include Health Analytics powered by Cognitio’s Health Data Factory that drives better care outcomes and higher ROI on care spending. We specialize in providing Data Governance solutions that help effectively use data in a consistent and compliant manner. Additionally, our smart intelligence solutions enable a deeper understanding of operations through the use of data science and advanced solutions like process mining technologies. We have offices in New Jersey and Connecticut in the USA and in Gurgaon in India.
What we're looking for:
- Ability in data modelling, design, build and deploy DW/BI systems for Insurance, Health Care, Banking, etc.
- Performance tuning of ETL process and SQL queries and recommend & implement ETL and query tuning techniques.
- Develop and create transformation queries, views, and stored procedures for ETL processes, and process automations.
- Translate business needs into technical specifications, evaluate, and improve existing BI systems.
- Use business intelligence and visualization software (e.g., Tableau, Qlik Sense, Power BI etc.) to empower customers to drive their analytics and reporting
- Develop and update technical documentation for BI systems.
Key Technical Skills:
- Hands on experience in MS SQL Server & MSBI (SSIS/SSRS/SSAS), with understanding of database concepts, star schema, SQL Tuning, OLAP, Databricks, Hadoop, Spark, cloud technologies.
- Experience in designing and building complete ETL / SSIS processes and transforming data for ODS, Staging, and Data Warehouse
- Experience building self-service reporting solutions using business intelligence software (e.g., Tableau, Qlik Sense, Power BI etc.)
About Us
Mindtickle provides a comprehensive, data-driven solution for sales readiness and enablement that fuels revenue growth and brand value for dozens of Fortune 500 and Global 2000 companies and hundreds of the world’s most recognized companies across technology, life sciences, financial services, manufacturing, and service sectors.
With purpose-built applications, proven methodologies, and best practices designed to drive effective sales onboarding and ongoing readiness, mindtickle enables company leaders and sellers to continually assess, diagnose and develop the knowledge, skills, and behaviors required to engage customers and drive growth effectively. We are funded by great investors, like – Softbank, Canaan partners, NEA, Accel Partners, and others.
Job Brief
We are looking for a rockstar researcher at the Center of Excellence for Machine Learning. You are responsible for thinking outside the box, crafting new algorithms, developing end-to-end artificial intelligence-based solutions, and rightly selecting the most appropriate architecture for the system(s), such that it suits the business needs, and achieves the desired results under given constraints.
Credibility:
- You must have a proven track record in research and development with adequate publication/patenting and/or academic credentials in data science.
- You have the ability to directly connect business problems to research problems along with the latest emerging technologies.
Strategic Responsibility:
- To perform the following: understanding problem statements, connecting the dots between high-level business statements and deep technology algorithms, crafting new systems and methods in the space of structured data mining, natural language processing, computer vision, speech technologies, robotics or Internet of things etc.
- To be responsible for end-to-end production level coding with data science and machine learning algorithms, unit and integration testing, deployment, optimization and fine-tuning of models on cloud, desktop, mobile or edge etc.
- To learn in a continuous mode, upgrade and upskill along with publishing novel articles in journals and conference proceedings and/or filing patents, and be involved in evangelism activities and ecosystem development etc.
- To share knowledge, mentor colleagues, partners, and customers, take sessions on artificial intelligence topics both online or in-person, participate in workshops, conferences, seminars/webinars as a speaker, instructor, demonstrator or jury member etc.
- To design and develop high-volume, low-latency applications for mission-critical systems and deliver high availability and performance.
- To collaborate within the product streams and team to bring best practices and leverage world-class tech stack.
- To set up every essentials (tracking / alerting) to make sure the infrastructure / software built is working as expected.
- To search, collect and clean Data for analysis and setting up efficient storage and retrieval pipelines.
Personality:
- Requires excellent communication skills – written, verbal, and presentation.
- You should be a team player.
- You should be positive towards problem-solving and have a very structured thought process to solve problems.
- You should be agile enough to learn new technology if needed.
Qualifications:
- B Tech / BS / BE / M Tech / MS / ME in CS or equivalent from Tier I / II or Top Tier Engineering Colleges and Universities.
- 6+ years of strong software (application or infrastructure) development experience and software engineering skills (Python, R, C, C++ / Java / Scala / Golang).
- Deep expertise and practical knowledge of operating systems, MySQL and NoSQL databases(Redis/couchbase/mongodb/ES or any graphDB).
- Good understanding of Machine Learning Algorithms, Linear Algebra and Statistics.
- Working knowledge of Amazon Web Services(AWS).
- Experience with Docker and Kubernetes will be a plus.
- Experience with Natural Language Processing, Recommendation Systems, or Search Engines.
Our Culture
As an organization, it’s our priority to create a highly engaging and rewarding workplace. We offer tons of awesome perks, great learning opportunities & growth.
Our culture reflects the globally diverse backgrounds of our employees along with our commitment to our customers, each other, and a passion for excellence.
To know more about us, feel free to go through these videos:
1. Sales Readiness Explained: https://www.youtube.com/watch?v=XyMJj9AlNww&t=6s
2. What We Do: https://www.youtube.com/watch?v=jv3Q2XgnkBY
3. Ready to Close More Deals, Faster: https://www.youtube.com/watch?v=nB0exreVU-s
To view more videos, please access the below-mentioned link:
https://www.youtube.com/c/mindtickle/videos
Mindtickle is proud to be an Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, or any other characteristic protected by law.
Your Right to Work - In compliance with applicable laws, all persons hired will be required to verify identity and eligibility to work in the respective work locations and to complete the required employment eligibility verification document form upon hire.
Senior Data Scientist
Your goal: To improve the education process and improve the student experience through data.
The organization: Data Science for Learning Services Data Science and Machine Learning are core to Chegg. As a Student Hub, we want to ensure that students discover the full breadth of learning solutions we have to offer to get full value on their learning time with us. To create the most relevant and engaging interactions, we are solving a multitude of machine learning problems so that we can better model student behavior, link various types of content, optimize workflows, and provide a personalized experience.
The Role: Senior Data Scientist
As a Senior Data Scientist, you will focus on conducting research and development in NLP and ML. You will be responsible for writing production-quality code for data product solutions at Chegg. You will lead in identification and implementation of key projects to process data and knowledge discovery.
Responsibilities:
• Translate product requirements into AIML/NLP solutions
• Be able to think out of the box and be able to design novel solutions for the problem at hand
• Write production-quality code
• Be able to design data and annotation collection strategies
• Identify key evaluation metrics and release requirements for data products
• Integrate new data and design workflows
• Innovate, share, and educate team members and community
Requirements:
• Working experience in machine learning, NLP, recommendation systems, experimentation, or related fields, with a specialization in NLP • Working experience on large language models that cater to multiple tasks such as text generation, Q&A, summarization, translation etc is highly preferred
• Knowledge on MLOPs and deployment pipelines is a must
• Expertise on supervised, unsupervised and reinforcement ML algorithms.
• Strong programming skills in Python
• Top data wrangling skills using SQL or NOSQL queries
• Experience using containers to deploy real-time prediction services
• Passion for using technology to help students
• Excellent communication skills
• Good team player and a self-starter
• Outstanding analytical and problem-solving skills
• Experience working with ML pipeline products such as AWS Sagemaker, Google ML, or Databricks a plus.
Why do we exist?
Students are working harder than ever before to stabilize their future. Our recent research study called State of the Student shows that nearly 3 out of 4 students are working to support themselves through college and 1 in 3 students feel pressure to spend more than they can afford. We founded our business on provided affordable textbook rental options to address these issues. Since then, we’ve expanded our offerings to supplement many facets of higher educational learning through Chegg Study, Chegg Math, Chegg Writing, Chegg Internships, Thinkful Online Learning, and more, to support students beyond their college experience. These offerings lower financial concerns for students by modernizing their learning experience. We exist so students everywhere have a smarter, faster, more affordable way to student.
Video Shorts
Life at Chegg: https://jobs.chegg.com/Video-Shorts-Chegg-Services
Certified Great Place to Work!: http://reviews.greatplacetowork.com/chegg
Chegg India: http://www.cheggindia.com/
Chegg Israel: http://insider.geektime.co.il/organizations/chegg
Thinkful (a Chegg Online Learning Service): https://www.thinkful.com/about/#careers
Chegg out our culture and benefits!
http://www.chegg.com/jobs/benefits
https://www.youtube.com/watch?v=YYHnkwiD7Oo
Chegg is an equal-opportunity employer
1) Understand the business objectives, formulate hypotheses and collect the relevant data using SQL/R/Python. Analyse bureau, customer and lending performance data on a periodic basis to generate insights. Present complex information and data in an uncomplicated, easyto-understand way to drive action.
2) Independently Build and refit robust models for achieving game-changing growth while managing risk.
3) Identify and implement new analytical/modelling techniques to improve model performance across customer lifecycle (acquisitions, management, fraud, collections, etc.
4) Help define the data infrastructure strategy for Indian subsidiary.
a. Monitor data quality and quantity.
b. Define a strategy for acquisition, storage, retention, and retrieval of data elements. e.g.: Identify new data types and collaborate with technology teams to capture them.
c. Build a culture of strong automation and monitoring
d. Staying connected to the Analytics industry trends - data, techniques, technology, etc. and leveraging them to continuously evolve data science standards at Credit Saison.
Required Skills & Qualifications:
1) 3+ years working in data science domains with experience in building risk models. Fintech/Financial analysis experience is required.
2) Expert level proficiency in Analytical tools and languages such as SQL, Python, R/SAS, VBA etc.
3) Experience with building models using common modelling techniques (Logistic and linear regressions, decision trees, etc.)
4) Strong familiarity with Tableau//Power BI/Qlik Sense or other data visualization tools
5) Tier 1 college graduate (IIT/IIM/NIT/BITs preferred).
6) Demonstrated autonomy, thought leadership, and learning agility.
- Experience implementing large-scale ETL processes using Informatica PowerCenter.
- Design high-level ETL process and data flow from the source system to target databases.
- Strong experience with Oracle databases and strong SQL.
- Develop & unit test Informatica ETL processes for optimal performance utilizing best practices.
- Performance tune Informatica ETL mappings and report queries.
- Develop database objects like Stored Procedures, Functions, Packages, and Triggers using SQL and PL/SQL.
- Hands-on Experience in Unix.
- Experience in Informatica Cloud (IICS).
- Work with appropriate leads and review high-level ETL design, source to target data mapping document, and be the point of contact for any ETL-related questions.
- Good understanding of project life cycle, especially tasks within the ETL phase.
- Ability to work independently and multi-task to meet critical deadlines in a rapidly changing environment.
- Excellent communication and presentation skills.
- Effectively worked on the Onsite and Offshore work model.
● Frame ML / AI use cases that can improve the company’s product
● Implement and develop ML / AI / Data driven rule based algorithms as software items
● For example, building a chatbot that replies an answer from relevant FAQ, and
reinforcing the system with a feedback loop so that the bot improves
Must have skills:
● Data extraction and ETL
● Python (numpy, pandas, comfortable with OOP)
● Django
● Knowledge of basic Machine Learning / Deep Learning / AI algorithms and ability to
implement them
● Good understanding of SDLC
● Deployed ML / AI model in a mobile / web product
● Soft skills : Strong communication skills & Critical thinking ability
Good to have:
● Full stack development experience
Required Qualification:
B.Tech. / B.E. degree in Computer Science or equivalent software engineering
Intro
Our data and risk team is the core pillar of our business that harnesses alternative data sources to guide the decisions we make at Rely. The team designs, architects, as well as develop and maintain a scalable data platform the powers our machine learning models. Be part of a team that will help millions of consumers across Asia, to be effortlessly in control of their spending and make better decisions.
What will you do
The data engineer is focused on making data correct and accessible, and building scalable systems to access/process it. Another major responsibility is helping AI/ML Engineers write better code.
• Optimize and automate ingestion processes for a variety of data sources such as: click stream, transactional and many other sources.
- Create and maintain optimal data pipeline architecture and ETL processes
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Develop data pipeline and infrastructure to support real-time decisions
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data' technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs.
What will you need
• 2+ hands-on experience building and implementation of large scale production pipeline and Data Warehouse
• Experience dealing with large scale
- Proficiency in writing and debugging complex SQLs
- Experience working with AWS big data tools
• Ability to lead the project and implement best data practises and technology
Data Pipelining
- Strong command in building & optimizing data pipelines, architectures and data sets
- Strong command on relational SQL & noSQL databases including Postgres
- Data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
Big Data: Strong experience in big data tools & applications
- Tools: Hadoop, Spark, HDFS etc
- AWS cloud services: EC2, EMR, RDS, Redshift
- Stream-processing systems: Storm, Spark-Streaming, Flink etc.
- Message queuing: RabbitMQ, Spark etc
Software Development & Debugging
- Strong experience in object-oriented programming/object function scripting languages: Python, Java, C++, Scala, etc
- Strong hold on data structures & algorithms
What would be a bonus
- Prior experience working in a fast-growth Startup
- Prior experience in the payments, fraud, lending, advertising companies dealing with large scale data