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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.
Roles and Responsibilities:
- 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
Requirements:
- 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
Qualifications :
- Minimum 2 years of .NET development experience (ASP.Net 3.5 or greater and C# 4 or greater).
- Good knowledge of MVC, Entity Framework, and Web API/WCF.
- ASP.NET Core knowledge is preferred.
- Creating APIs / Using third-party APIs
- Working knowledge of Angular is preferred.
- Knowledge of Stored Procedures and experience with a relational database (MSSQL 2012 or higher).
- Solid understanding of object-oriented development principles
- Working knowledge of web, HTML, CSS, JavaScript, and the Bootstrap framework
- Strong understanding of object-oriented programming
- Ability to create reusable C# libraries
- Must be able to write clean comments, readable C# code, and the ability to self-learn.
- Working knowledge of GIT
Qualities required :
Over above tech skill we prefer to have
- Good communication and Time Management Skill.
- Good team player and ability to contribute on a individual basis.
- We provide the best learning and growth environment for candidates.
Skills:
NET Core
.NET Framework
ASP.NET Core
ASP.NET MVC
ASP.NET Web API
C#
HTML
We are looking out for a technically driven "ML OPS Engineer" for one of our premium client
COMPANY DESCRIPTION:
Key Skills
• Excellent hands-on expert knowledge of cloud platform infrastructure and administration
(Azure/AWS/GCP) with strong knowledge of cloud services integration, and cloud security
• Expertise setting up CI/CD processes, building and maintaining secure DevOps pipelines with at
least 2 major DevOps stacks (e.g., Azure DevOps, Gitlab, Argo)
• Experience with modern development methods and tooling: Containers (e.g., docker) and
container orchestration (K8s), CI/CD tools (e.g., Circle CI, Jenkins, GitHub actions, Azure
DevOps), version control (Git, GitHub, GitLab), orchestration/DAGs tools (e.g., Argo, Airflow,
Kubeflow)
• Hands-on coding skills Python 3 (e.g., API including automated testing frameworks and libraries
(e.g., pytest) and Infrastructure as Code (e.g., Terraform) and Kubernetes artifacts (e.g.,
deployments, operators, helm charts)
• Experience setting up at least one contemporary MLOps tooling (e.g., experiment tracking,
model governance, packaging, deployment, feature store)
• Practical knowledge delivering and maintaining production software such as APIs and cloud
infrastructure
• Knowledge of SQL (intermediate level or more preferred) and familiarity working with at least
one common RDBMS (MySQL, Postgres, SQL Server, Oracle)
- Data Engineer
Required skill set: AWS GLUE, AWS LAMBDA, AWS SNS/SQS, AWS ATHENA, SPARK, SNOWFLAKE, PYTHON
Mandatory Requirements
- Experience in AWS Glue
- Experience in Apache Parquet
- Proficient in AWS S3 and data lake
- Knowledge of Snowflake
- Understanding of file-based ingestion best practices.
- Scripting language - Python & pyspark
CORE RESPONSIBILITIES
- Create and manage cloud resources in AWS
- Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies
- Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform
- Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations
- Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
- Define process improvement opportunities to optimize data collection, insights and displays.
- Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible
- Identify and interpret trends and patterns from complex data sets
- Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders.
- Key participant in regular Scrum ceremonies with the agile teams
- Proficient at developing queries, writing reports and presenting findings
- Mentor junior members and bring best industry practices
QUALIFICATIONS
- 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales)
- Strong background in math, statistics, computer science, data science or related discipline
- Advanced knowledge one of language: Java, Scala, Python, C#
- Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake
- Proficient with
- Data mining/programming tools (e.g. SAS, SQL, R, Python)
- Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
- Data visualization (e.g. Tableau, Looker, MicroStrategy)
- Comfortable learning about and deploying new technologies and tools.
- Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines.
- Good written and oral communication skills and ability to present results to non-technical audiences
- Knowledge of business intelligence and analytical tools, technologies and techniques.
Familiarity and experience in the following is a plus:
- AWS certification
- Spark Streaming
- Kafka Streaming / Kafka Connect
- ELK Stack
- Cassandra / MongoDB
- CI/CD: Jenkins, GitLab, Jira, Confluence other related tools
Skills and requirements
- Experience analyzing complex and varied data in a commercial or academic setting.
- Desire to solve new and complex problems every day.
- Excellent ability to communicate scientific results to both technical and non-technical team members.
Desirable
- A degree in a numerically focused discipline such as, Maths, Physics, Chemistry, Engineering or Biological Sciences..
- Hands on experience on Python, Pyspark, SQL
- Hands on experience on building End to End Data Pipelines.
- Hands on Experience on Azure Data Factory, Azure Data Bricks, Data Lake - added advantage
- Hands on Experience in building data pipelines.
- Experience with Bigdata Tools, Hadoop, Hive, Sqoop, Spark, SparkSQL
- Experience with SQL or NoSQL databases for the purposes of data retrieval and management.
- Experience in data warehousing and business intelligence tools, techniques and technology, as well as experience in diving deep on data analysis or technical issues to come up with effective solutions.
- BS degree in math, statistics, computer science or equivalent technical field.
- Experience in data mining structured and unstructured data (SQL, ETL, data warehouse, Machine Learning etc.) in a business environment with large-scale, complex data sets.
- Proven ability to look at solutions in unconventional ways. Sees opportunities to innovate and can lead the way.
- Willing to learn and work on Data Science, ML, AI.
Duration : Full Time
Location : Vishakhapatnam, Bangalore, Chennai
years of experience : 3+ years
Job Description :
- 3+ Years of working as a Data Engineer with thorough understanding of data frameworks that collect, manage, transform and store data that can derive business insights.
- Strong communications (written and verbal) along with being a good team player.
- 2+ years of experience within the Big Data ecosystem (Hadoop, Sqoop, Hive, Spark, Pig, etc.)
- 2+ years of strong experience with SQL and Python (Data Engineering focused).
- Experience with GCP Data Services such as BigQuery, Dataflow, Dataproc, etc. is an added advantage and preferred.
- Any prior experience in ETL tools such as DataStage, Informatica, DBT, Talend, etc. is an added advantage for the role.
Role Summary
We Are looking for an analytically inclined, Insights Driven Product Analyst to make our organisation more data driven. In this role you will be responsible for creating dashboards to drive insights for product and business teams. Be it Day to Day decisions as well as long term impact assessment, Measuring the Efficacy of different products or certain teams, You'll be Empowering each of them. The growing nature of the team will require you to be in touch with all of the teams at upgrad. Are you the "Go-To" person everyone looks at for getting Data, Then this role is for you.
Roles & Responsibilities
- Lead and own the analysis of highly complex data sources, identifying trends and patterns in data and provide insights/recommendations based on analysis results
- Build, maintain, own and communicate detailed reports to assist Marketing, Growth/Learning Experience and Other Business/Executive Teams
- Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
- Analyze data and generate insights in the form of user analysis, user segmentation, performance reports, etc.
- Facilitate review sessions with management, business users and other team members
- Design and create visualizations to present actionable insights related to data sets and business questions at hand
- Develop intelligent models around channel performance, user profiling, and personalization
Skills Required
- Having 4-6 yrs hands-on experience with Product related analytics and reporting
- Experience with building dashboards in Tableau or other data visualization tools such as D3
- Strong data, statistics, and analytical skills with a good grasp of SQL.
- Programming experience in Python is must
- Comfortable managing large data sets
- Good Excel/data management skills
CommerceIQ is Hiring Data Scientist (3-5 yrs)
At CommerceIQ, we are building the world’s most sophisticated E-commerce Channel Optimization software to help brands leverage Machine Learning, Analytics and Automation to grow their E-commerce business on all channels, globally.
Using CommerceIQ as a single source of truth, customers have driven 40% increase in incremental sales, 20% improvement in profitability and 32% reduction in out of stock rates on Amazon.
What You’ll Be Doing
As a Senior Data Scientist, you will work closely with Engineering/Product/Operations teams to build state-of-the-art ML based solutions for B2B SaaS products. This entails not only leveraging advanced techniques for predictions, time-series forecasting, topic modelling, optimisation but deep understanding of business and product too.
- Apply excellent problem solving skills to deconstruct and formulate solutions from first-principles
- Work on data science roadmap and build the core engine of our flagship CommerceIQ product
- Collaborate with product and engineering to design product strategy, identify key metrics to drive and support with proof of concept
- Perform rapid prototyping of experimental solutions and develop robust, sustainable and scalable production systems
- Work with large scale ecommerce data of the biggest brands on amazon
- Apply out-of-the-box, advanced algorithms to complex problems in real-time systems
- Drive productization of techniques to be made available to a wide range of customers
- You would be working with and mentoring fellow team members on the owned charter
What we are looking for -
- Bachelor’s or Masters in Computer Science or Maths/Stats from a reputed college with 4+ years of experience in solving data science problems that have driven value to customers
- Good depth and breadth in machine learning (theory and practice), optimization methods, data mining, statistics and linear algebra. Experience in NLP would be an advantage
- Hands-on programming skills and ability to write modular and scalable code in Python/R. Knowledge of SQL is required
- Familiarity with distributed computing architecture like Spark, Map-Reduce paradigm and Hadoop will be an added advantage
- Strong spoken and written communication skills, able to explain complex ideas in a simple, intuitive manner, write/maintain good technical documentation on projects
- Experience with building ML data products in an engineering organization interfacing with other teams and departments to deliver impact
- We are looking for candidates who are curious and self-starters; obsess over customer problems to deliver maximum value to them.
- Data scientist, Machine Learning, data science, data analyst
Job Type: Full-time
Experience:
- Data Scientist: 3 years (Required)
Application Question:
- Looking for product based industry experience from tier 1 /tier 2 colleges (NIT ,BIT, IIT,IIIT, BITS, Strong Profiles)
Octro Inc. is looking for a Data Scientist who will support the product, leadership and marketing teams with insights gained from analyzing multiple sources of data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.
They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights.
They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
Responsibilities :
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Mine and analyze data from multiple databases to drive optimization and improvement of product development, marketing techniques and business strategies.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Develop custom data models and algorithms to apply to data sets.
- Use predictive modelling to increase and optimize user experiences, revenue generation, ad targeting and other business outcomes.
- Develop various A/B testing frameworks and test model qualities.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
Qualifications :
- Strong problem solving skills with an emphasis on product development and improvement.
- Advanced knowledge of SQL and its use in data gathering/cleaning.
- Experience using statistical computer languages (R, Python, etc.) to manipulate data and draw insights from large data sets.
- Experience working with and creating data architectures.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Excellent written and verbal communication skills for coordinating across teams.