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• Key responsibility is to design & develop a data pipeline for real-time data integration, processing, executing of the model (if required), and exposing output via MQ / API / No-SQL DB for consumption
• Provide technical expertise to design efficient data ingestion solutions to store & process unstructured data, such as Documents, audio, images, weblogs, etc
• Developing API services to provide data as a service
• Prototyping Solutions for complex data processing problems using AWS cloud-native solutions
• Implementing automated Audit & Quality assurance Checks in Data Pipeline
• Document & maintain data lineage from various sources to enable data governance
• Coordination with BIU, IT, and other stakeholders to provide best-in-class data pipeline solutions, exposing data via APIs, loading in down streams, No-SQL Databases, etc

Skills

• Programming experience using Python & SQL
• Extensive working experience in Data Engineering projects, using AWS Kinesys,  AWS S3, DynamoDB, EMR, Lambda, Athena, etc for event processing
• Experience & expertise in implementing complex data pipeline
• Strong Familiarity with AWS Toolset for Storage & Processing. Able to recommend the right tools/solutions available to address specific data processing problems
• Hands-on experience in Unstructured (Audio, Image, Documents, Weblogs, etc) Data processing.
• Good analytical skills with the ability to synthesize data to design and deliver meaningful information
• Know-how on any No-SQL DB (DynamoDB, MongoDB, CosmosDB, etc) will be an advantage.
• Ability to understand business functionality, processes, and flows
• Good combination of technical and interpersonal skills with strong written and verbal communication; detail-oriented with the ability to work independently

Functional knowledge

• Real-time Event Processing
• Data Governance & Quality assurance
• Containerized deployment
• Linux
• Unstructured Data Processing
• AWS Toolsets for Storage & Processing
• Data Security

• 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

The Data Engineering team is one of the core technology teams of Lumiq.ai and is responsible for creating all the Data related products and platforms which scale for any amount of data, users, and processing. The team also interacts with our customers to work out solutions, create technical architectures and deliver the products and solutions.

If you are someone who is always pondering how to make things better, how technologies can interact, how various tools, technologies, and concepts can help a customer or how a customer can use our products, then Lumiq is the place of opportunities.

Who are you?

• Enthusiast is your middle name. You know what’s new in Big Data technologies and how things are moving
• Apache is your toolbox and you have been a contributor to open source projects or have discussed the problems with the community on several occasions
• You use cloud for more than just provisioning a Virtual Machine
• Vim is friendly to you and you know how to exit Nano
• You check logs before screaming about an error
• You are a solid engineer who writes modular code and commits in GIT
• You are a doer who doesn’t say “no” without first understanding
• You understand the value of documentation of your work
• You are familiar with Machine Learning Ecosystem and how you can help your fellow Data Scientists to explore data and create production-ready ML pipelines

Experience

• At least 2 years of Data Engineering Experience
• Have interacted with Customers

Must Have Skills

• Amazon Web Services (AWS) - EMR, Glue, S3, RDS, EC2, Lambda, SQS, SES
• Apache Spark
• Python
• Scala
• PostgreSQL
• Git
• Linux

Good to have Skills

• Apache NiFi
• Apache Kafka
• Apache Hive
• Docker
• Amazon Certification

This profile will include the following responsibilities:

- Develop Parsers for XML and JSON Data sources/feeds

- Write Automation Scripts for product development

- Build API Integrations for 3^rd Party product integration

- Perform Data Analysis

- Research on Machine learning algorithms

- Understand AWS cloud architecture and work with 3 party vendors for deployments

• Collaborate with the business teams to understand the data environment in the organization; develop and lead the Data Scientists team to test and scale new algorithms through pilots and subsequent scaling up of the solutions
• Influence, build and maintain the large-scale data infrastructure required for the AI projects, and integrate with external IT infrastructure/service
• Act as the single point source for all data related queries; strong understanding of internal and external data sources; provide inputs in deciding data-schemas
• Design, develop and maintain the framework for the analytics solutions pipeline
• Provide inputs to the organization’s initiatives on data quality and help implement frameworks and tools for the various related initiatives
• Work in cross-functional teams of software/machine learning engineers, data scientists, product managers, and others to build the AI ecosystem
• Collaborate with the external organizations including vendors, where required, in respect of all data-related queries as well as implementation initiatives

Job Details:-

Designation - Data Scientist

Urgently required. (NP of maximum 15 days)

Location:- Mumbai

Experience:- 5-7 years.

Package Offered:- Rs.5,00,000/- to Rs.9,00,000/- pa.

Data Scientist

Job Description:-

Responsibilities:

• Identify valuable data sources and automate collection processes
• Undertake preprocessing of structured and unstructured data
• Analyze large amounts of information to discover trends and patterns
• Build predictive models and machine-learning algorithms
• Combine models through ensemble modeling
• Present information using data visualization techniques
• Propose solutions and strategies to business challenges
• Collaborate with engineering and product development teams

Requirements:

• Proven experience as a Data Scientist or Data Analyst
• Experience in data mining
• Understanding of machine-learning and operations research
• Knowledge of R, SQL and Python; familiarity with Scala, Java is an asset
• Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
• Analytical mind and business acumen
• Strong math skills (e.g. statistics, algebra)
• Problem-solving aptitude
• Excellent communication and presentation skills
• BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred

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 and information extraction from clinical notes.

This is a role for highly technical machine learning & 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 machine learning models 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.

What you will achieve:

• Define the research vision for data science, and oversee planning, staffing, and prioritization to make sure the team is advancing that roadmap

• Invest in your team’s skills, tools, and processes to improve their velocity, including working with engineering counterparts to shape the roadmap for machine learning needs

• Hire, retain, and develop talented and diverse staff through ownership of our data science hiring processes, brand, and functional leadership of data scientists

• Evangelise machine learning and AI internally and externally, including attending conferences and being a thought leader in the space

• Partner with the executive team and other business leaders to deliver cross-functional research work and models

Required Skills:

• Strong background in classical machine learning and machine learning deployments is a must and preferably with 4-8 years of experience

• Knowledge of deep learning & NLP

• Hands-on experience in TensorFlow/PyTorch, Scikit-Learn, Python, Apache Spark & Big Data platforms to manipulate large-scale structured and unstructured datasets.

• Experience with GPU computing is a plus.

• Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization. This could be through technical leadership with ownership over a research agenda, or developing a team as a personnel manager in a new area at a larger company.

• Expert-level experience with a wide range of quantitative methods that can be applied to business problems.

• Evidence you’ve successfully been able to scope, deliver and sell your own research in a way that shifts the agenda of a large organization.

• Excellent written and verbal communication skills on quantitative topics for a variety of audiences: product managers, designers, engineers, and business leaders.

• Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling

Qualifications

• Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization

• Expert-level experience with machine learning that can be applied to business problems

• Evidence you’ve successfully been able to scope, deliver and sell your own work in a way that shifts the agenda of a large organization

• Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling

• Degree in a field that has very applicable use of data science / statistics techniques (e.g. statistics, applied math, computer science, OR a science field with direct statistics application)

• 5+ years of industry experience in data science and machine learning, preferably at a software product company

• 3+ years of experience managing data science teams, incl. managing/grooming managers beneath you

• 3+ years of experience partnering with executive staff on data topics