Data Scientist

As a part of WWS, your expertise in machine learning helps us extract value from our data. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and situating them to production. The ideal candidate will be passionate about artificial intelligence and stay up-to-date with the latest developments in the field.

What We Expect

• A Bachelor's/Master's degree in IT, computer science, or an advanced related field is preferred.

• At least 3+ years of experience working with ML libraries and packages.

• Familiarity with coding and programming languages, including Python, Java, C++, and SAS.

• Strong experience in programming and statistics.

• Well-versed in Data Science and neural schematics in networking and software.

• Flexibility in shifts is appreciated.

A Full Stack Developer’s Ideal Day At WWS

Design and Develop. The primary protocols include implementing machine learning algorithms and running AI systems experiments and tests. The Designing and development of machine learning systems along with performing statistical analyses falls under day to day activities of the developer.

Algorithm Assertion. The engineers act as critical members of the data science team as their tasks involve researching, asserting, and designing the artificial intelligence responsible for machine learning and maintaining and improving existing artificial intelligence systems.

Research and Development. To analyze large, complex datasets and extract insights and decide on the appropriate technique. research and implement best practices to improve the existing machine learning infrastructure. At most providing support to engineers and product managers in implementing machine learning as the product.

What You Can Expect

• Full-time, salaried positions creamed with welfare programs.

• Competitive salary and tailored training in the core space with recognition potential and annual bonus.

• Periodic performance appraisals.

• Attendance Incentives.

• Working with the best and budding talent in the industry.

• A conducive intangible environment with dynamic benefits.

Why Consider Machine Learning Engineer as a career with WWS?

With a very appealing work environment at WWS, our setting made it easier to build relationships with other staff members and clients. You may also have an opportunity to learn other aspects of environmental office work on the job, which can enhance your experience and qualifications.

Many businesses must proactively react to changing factors — like patterns of customer behavior or prices. Tracking model performance and retraining it once fresher data is available is key to success. This falls under the MLE range of responsibilities for which the requirement has been crucial for many organizations.

Please attach your resume and let us know through email your current address, phone number, and the best time to contact you by phone.

                                          Apply To this Job

Job Title – Data Scientist (Forecasting)

Anicca Data is seeking a Data Scientist (Forecasting) who is motivated to apply his/her/their skill set to solve complex and challenging problems. The focus of the role will center around applying deep learning models to real-world applications.  The candidate should have experience in training, testing deep learning architectures.  This candidate is expected to work on existing codebases or write an optimized codebase at Anicca Data. The ideal addition to our team is self-motivated, highly organized, and a team player who thrives in a fast-paced environment with the ability to learn quickly and work independently.

Job Location: Remote (for time being) and Bangalore, India (post-COVID crisis)

• At least 3+ years of experience in a Data Scientist role
• Bachelor's/Master’s degree in Computer Science, Engineering, Statistics, Mathematics, or similar quantitative discipline. D. will add merit to the application process
• Experience with large data sets, big data, and analytics
• Exposure to statistical modeling, forecasting, and machine learning. Deep theoretical and practical knowledge of deep learning, machine learning, statistics, probability, time series forecasting
• Training Machine Learning (ML) algorithms in areas of forecasting and prediction
• Experience in developing and deploying machine learning solutions in a cloud environment (AWS, Azure, Google Cloud) for production systems
• Research and enhance existing in-house, open-source models, integrate innovative techniques, or create new algorithms to solve complex business problems
• Experience in translating business needs into problem statements, prototypes, and minimum viable products
• Experience managing complex projects including scoping, requirements gathering, resource estimations, sprint planning, and management of internal and external communication and resources
• Write C++ and Python code along with TensorFlow, PyTorch to build and enhance the platform that is used for training ML models

Preferred Experience

• Worked on forecasting projects – both classical and ML models
• Experience with training time series forecasting methods like Moving Average (MA) and Autoregressive Integrated Moving Average (ARIMA) with Neural Networks (NN) models as Feed-forward NN and Nonlinear Autoregressive
• Strong background in forecasting accuracy drivers
• Experience in Advanced Analytics techniques such as regression, classification, and clustering
• Ability to explain complex topics in simple terms, ability to explain use cases and tell stories

AWS Glue Developer 

Work Experience: 6 to 8 Years

Work Location:  Noida, Bangalore, Chennai & Hyderabad

Must Have Skills: AWS Glue, DMS, SQL, Python, PySpark, Data integrations and Data Ops, 

Job Reference ID:BT/F21/IND

Job Description:

Design, build and configure applications to meet business process and application requirements.

Responsibilities:

7 years of work experience with ETL, Data Modelling, and Data Architecture Proficient in ETL optimization, designing, coding, and tuning big data processes using Pyspark Extensive experience to build data platforms on AWS using core AWS services Step function, EMR, Lambda, Glue and Athena, Redshift, Postgres, RDS etc and design/develop data engineering solutions. Orchestrate using Airflow.

Technical Experience:

Hands-on experience on developing Data platform and its components Data Lake, cloud Datawarehouse, APIs, Batch and streaming data pipeline Experience with building data pipelines and applications to stream and process large datasets at low latencies.

➢ Enhancements, new development, defect resolution and production support of Big data ETL development using AWS native services.

➢ Create data pipeline architecture by designing and implementing data ingestion solutions.

➢ Integrate data sets using AWS services such as Glue, Lambda functions/ Airflow.

➢ Design and optimize data models on AWS Cloud using AWS data stores such as Redshift, RDS, S3, Athena.

➢ Author ETL processes using Python, Pyspark.

➢ Build Redshift Spectrum direct transformations and data modelling using data in S3.

➢ ETL process monitoring using CloudWatch events.

➢ You will be working in collaboration with other teams. Good communication must.

➢ Must have experience in using AWS services API, AWS CLI and SDK

Professional Attributes:

➢ Experience operating very large data warehouses or data lakes Expert-level skills in writing and optimizing SQL Extensive, real-world experience designing technology components for enterprise solutions and defining solution architectures and reference architectures with a focus on cloud technology.

➢ Must have 6+ years of big data ETL experience using Python, S3, Lambda, Dynamo DB, Athena, Glue in AWS environment.

➢ Expertise in S3, RDS, Redshift, Kinesis, EC2 clusters highly desired.

Qualification:

➢ Degree in Computer Science, Computer Engineering or equivalent.

Salary: Commensurate with experience and demonstrated competence

• You're proficient in AI/Machine learning latest technologies  
• You're proficient in GPT-3 based algorithms 
• You have a passion for writing code as well as understanding and crafting the ways systems interact
• You believe in the benefits of agile processes and shipping code often
• You are pragmatic and work to coalesce requirements into reasonable solutions that provide value

• Deploy well-tested, maintainable and scalable software solutions
• Take end-to-end ownership of the technology stack and product 
• Collaborate with other engineers to architect scalable technical solutions
• Embrace and improve our standards and processes to reduce friction and unlock efficiency

Job Description

We are looking for an experienced engineer with superb technical skills. Primarily be responsible for architecting and building large scale data pipelines that delivers AI and Analytical solutions to our customers. The right candidate will enthusiastically take ownership in developing and managing a continuously improving, robust, scalable software solutions.

Although your primary responsibilities will be around back-end work, we prize individuals who are willing to step in and contribute to other areas including automation, tooling, and management applications. Experience with or desire to learn Machine Learning a plus.

Skills

• Bachelors/Masters/Phd in CS or equivalent industry experience
• Demonstrated expertise of building and shipping cloud native applications
• 5+ years of industry experience in administering (including setting up, managing, monitoring) data processing pipelines (both streaming and batch) using frameworks such as Kafka Streams, Py Spark, and streaming databases like druid or equivalent like Hive
• Strong industry expertise with containerization technologies including kubernetes (EKS/AKS), Kubeflow
• Experience with cloud platform services such as AWS, Azure or GCP especially with EKS, Managed Kafka
• 5+ Industry experience in python
• Experience with popular modern web frameworks such as Spring boot, Play framework, or Django
• Experience with scripting languages. Python experience highly desirable. Experience in API development using Swagger
• Implementing automated testing platforms and unit tests
• Proficient understanding of code versioning tools, such as Git
• Familiarity with continuous integration, Jenkins

Responsibilities

• Architect, Design and Implement Large scale data processing pipelines using Kafka Streams, PySpark, Fluentd and Druid
• Create custom Operators for Kubernetes, Kubeflow
• Develop data ingestion processes and ETLs
• Assist in dev ops operations
• Design and Implement APIs
• Identify performance bottlenecks and bugs, and devise solutions to these problems
• Help maintain code quality, organization, and documentation
• Communicate with stakeholders regarding various aspects of solution.
• Mentor team members on best practices

Introduction

http://www.synapsica.com/">Synapsica is a https://yourstory.com/2021/06/funding-alert-synapsica-healthcare-ivycap-ventures-endiya-partners/">series-A funded HealthTech startup founded by alumni from IIT Kharagpur, AIIMS New Delhi, and IIM Ahmedabad. We believe healthcare needs to be transparent and objective while being affordable. Every patient has the right to know exactly what is happening in their bodies and they don't have to rely on cryptic 2 liners given to them as a diagnosis. 

Towards this aim, we are building an artificial intelligence enabled cloud based platform to analyse medical images and create v2.0 of advanced radiology reporting.  We are backed by IvyCap, Endia Partners, YCombinator and other investors from India, US, and Japan. We are proud to have GE and The Spinal Kinetics as our partners. Here’s a small sample of what we’re building: https://www.youtube.com/watch?v=FR6a94Tqqls">https://www.youtube.com/watch?v=FR6a94Tqqls 

Your Roles and Responsibilities

We are looking for an experienced MLOps Engineer to join our engineering team and help us create dynamic software applications for our clients. In this role, you will be a key member of a team in decision making, implementations, development and advancement of ML operations of the core AI platform.

• Work closely with a cross functional team to serve business goals and objectives.
• Develop, Implement and Manage MLOps in cloud infrastructure for data preparation,deployment, monitoring and retraining models
• Design and build application containerisation and orchestrate with Docker and Kubernetes in AWS platform. 
• Build and maintain code, tools, packages in cloud

• At Least 2+ years of experience in Data engineering 
• At Least 3+ yr experience in Python with familiarity in popular ML libraries.
• At Least 2+ years experience in model serving and pipelines
• Working knowledge of containers like kubernetes , dockers, in AWS
• Design distributed systems deployment at scale
• Hands-on experience in coding and scripting
• Ability to write effective scalable and modular code.
• Familiarity with Git workflows, CI CD and NoSQL Mongodb
• Familiarity with Airflow, DVC and MLflow is a plus

• Must have 5-8 years of experience in handling data
• Must have the ability to interpret large amounts of data and to multi-task
• Must have strong knowledge of and experience with programming (Python), Linux/Bash scripting, databases(SQL, etc)
• Must have strong analytical and critical thinking to resolve business problems using data and tech
•  Must have domain familiarity and interest of – Cloud technologies (GCP/Azure Microsoft/ AWS Amazon), open-source technologies, Enterprise technologies
• Must have the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
• Must have good communication skills
• Working knowledge/exposure to ElasticSearch, PostgreSQL, Athena, PrestoDB, Jupyter Notebook