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Job Description
This requirement is to service our client which is a leading big data technology company that measures what viewers consume across platforms to enable marketers make better advertising decisions. We are seeking a Senior Data Operations Analyst to mine large-scale datasets for our client. Their work will have a direct impact on driving business strategies for prominent industry leaders. Self-motivation and strong communication skills are both must-haves. Ability to work in a fast-paced work environment is desired.
Problems being solved by our client:
Measure consumer usage of devices linked to the internet and home networks including computers, mobile phones, tablets, streaming sticks, smart TVs, thermostats and other appliances. There are more screens and other connected devices in homes than ever before, yet there have been major gaps in understanding how consumers interact with this technology. Our client uses a measurement technology to unravel dynamics of consumers’ interactions with multiple devices.
Duties and responsibilities:
- The successful candidate will contribute to the development of novel audience measurement and demographic inference solutions.
- Develop, implement, and support statistical or machine learning methodologies and processes.
- Build, test new features and concepts and integrate into production process
- Participate in ongoing research and evaluation of new technologies
- Exercise your experience in the development lifecycle through analysis, design, development, testing and deployment of this system
- Collaborate with teams in Software Engineering, Operations, and Product Management to deliver timely and quality data. You will be the knowledge expert, delivering quality data to our clients
Qualifications:
- 3-5 years relevant work experience in areas as outlined below
- Experience in extracting data using SQL from large databases
- Experience in writing complex ETL processes and frameworks for analytics and data management. Must have experience in working on ETL tools.
- Master’s degree or PhD in Statistics, Data Science, Economics, Operations Research, Computer Science, or a similar degree with a focus on statistical methods. A Bachelor’s degree in the same fields with significant, demonstrated professional research experience will also be considered.
- Programming experience in scientific computing language (R, Python, Julia) and the ability to interact with relational data (SQL, Apache Pig, SparkSQL). General purpose programming (Python, Scala, Java) and familiarity with Hadoop is a plus.
- Excellent verbal and written communication skills.
- Experience with TV or digital audience measurement or market research data is a plus.
- Familiarity with systems analysis or systems thinking is a plus.
- Must be comfortable with analyzing complex, high-volume and high-dimension data from varying sources
- Excellent verbal, written and computer communication skills
- Ability to engage with Senior Leaders across all functional departments
- Ability to take on new responsibilities and adapt to changes
Team:- We are a team of 9 data scientists working on Video Analytics Projects, Data Analytics projects for internal AI requirements of Reliance Industries as well for the external business. At a time, we make progress on multiple projects(atleast 4) in Video Analytics or Data Analytics.
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
-
Bachelor’s degree or greater in Computer Science, IT or related fields
-
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
Professional experience in Python – Mandatory experience
Basic knowledge of any BI Tool (Microsoft Power BI, Tableau etc.) and experience in R
will be an added advantage
Proficient in Excel
Good verbal and written communication skills
Key Responsibilities:
Analyze data trends and provide intelligent business insights, monitor operational and
business metrics
Complete ownership of business excellence dashboard and preparation of reports for
senior management stating trends, patterns, and predictions using relevant data
Review, validate and analyse data points and implement new data analysis
methodologies
Perform data profiling to identify and understand anomalies
Perform analysis to assess quality and meaning of data
Develop policies and procedures for the collection and analysis of data
Analyse existing process with the help of data and propose process change and/or lead
process re-engineering initiatives
Use BI Tools (Microsoft Power BI/Tableau) and develop and manage BI solutions
Responsibilities :
- Involve in planning, design, development and maintenance of large-scale data repositories, pipelines, analytical solutions and knowledge management strategy
- Build and maintain optimal data pipeline architecture to ensure scalability, connect operational systems data for analytics and business intelligence (BI) systems
- Build data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader
- Reporting and obtaining insights from large data chunks on import/export and communicating relevant pointers for helping in decision-making
- Preparation, analysis, and presentation of reports to the management for further developmental activities
- Anticipate, identify and solve issues concerning data management to improve data quality
Requirements :
- Ability to build and maintain ETL pipelines
- Technical Business Analysis experience and hands-on experience developing functional spec
- Good understanding of Data Engineering principles including data modeling methodologies
- Sound understanding of PostgreSQL
- Strong analytical and interpersonal skills as well as reporting capabilities
Minimum 4 to 14 Years OTM Technical / Functional experience
- Must have functional and techno-functional experience in OTM implementation and/or have supported projects dealing with these systems, and/or have worked on OTM Cloud
- Must have strong technical and functional knowledge of the latest OTM Application
- Must have knowledge of preparing mapping document to interface OTM system with EDI, WMS, order management and finance systems, and be able to translate the functional specifications into design specifications for the Offshore Delivery Centre
- Must have ability to write SQL statements for automation agents and other technical topics
- Hands on experience on JSPX/XSL will be additional advantage.
- Experience in end-to-end OTM life cycle/implementations/up-gradation and OTM architecture will be preferred
Specialism- Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, python, decision tree, random forest, SAS, clustering classification
Senior Analytics Consultant- Responsibilities
- Understand business problem and requirements by building domain knowledge and translate to data science problem
- Conceptualize and design cutting edge data science solution to solve the data science problem, apply design thinking concepts
- Identify the right algorithms , tech stack , sample outputs required to efficiently adder the end need
- Prototype and experiment the solution to successfully demonstrate the value
Independently or with support from team execute the conceptualized solution as per plan by following project management guidelines - Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization
- Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development , practice development initiatives
- Data Steward :
Data Steward will collaborate and work closely within the group software engineering and business division. Data Steward has overall accountability for the group's / Divisions overall data and reporting posture by responsibly managing data assets, data lineage, and data access, supporting sound data analysis. This role requires focus on data strategy, execution, and support for projects, programs, application enhancements, and production data fixes. Makes well-thought-out decisions on complex or ambiguous data issues and establishes the data stewardship and information management strategy and direction for the group. Effectively communicates to individuals at various levels of the technical and business communities. This individual will become part of the corporate Data Quality and Data management/entity resolution team supporting various systems across the board.
Primary Responsibilities:
- Responsible for data quality and data accuracy across all group/division delivery initiatives.
- Responsible for data analysis, data profiling, data modeling, and data mapping capabilities.
- Responsible for reviewing and governing data queries and DML.
- Accountable for the assessment, delivery, quality, accuracy, and tracking of any production data fixes.
- Accountable for the performance, quality, and alignment to requirements for all data query design and development.
- Responsible for defining standards and best practices for data analysis, modeling, and queries.
- Responsible for understanding end-to-end data flows and identifying data dependencies in support of delivery, release, and change management.
- Responsible for the development and maintenance of an enterprise data dictionary that is aligned to data assets and the business glossary for the group responsible for the definition and maintenance of the group's data landscape including overlays with the technology landscape, end-to-end data flow/transformations, and data lineage.
- Responsible for rationalizing the group's reporting posture through the definition and maintenance of a reporting strategy and roadmap.
- Partners with the data governance team to ensure data solutions adhere to the organization’s data principles and guidelines.
- Owns group's data assets including reports, data warehouse, etc.
- Understand customer business use cases and be able to translate them to technical specifications and vision on how to implement a solution.
- Accountable for defining the performance tuning needs for all group data assets and managing the implementation of those requirements within the context of group initiatives as well as steady-state production.
- Partners with others in test data management and masking strategies and the creation of a reusable test data repository.
- Responsible for solving data-related issues and communicating resolutions with other solution domains.
- Actively and consistently support all efforts to simplify and enhance the Clinical Trial Predication use cases.
- Apply knowledge in analytic and statistical algorithms to help customers explore methods to improve their business.
- Contribute toward analytical research projects through all stages including concept formulation, determination of appropriate statistical methodology, data manipulation, research evaluation, and final research report.
- Visualize and report data findings creatively in a variety of visual formats that appropriately provide insight to the stakeholders.
- Achieve defined project goals within customer deadlines; proactively communicate status and escalate issues as needed.
Additional Responsibilities:
- Strong understanding of the Software Development Life Cycle (SDLC) with Agile Methodologies
- Knowledge and understanding of industry-standard/best practices requirements gathering methodologies.
- Knowledge and understanding of Information Technology systems and software development.
- Experience with data modeling and test data management tools.
- Experience in the data integration project • Good problem solving & decision-making skills.
- Good communication skills within the team, site, and with the customer
Knowledge, Skills and Abilities
- Technical expertise in data architecture principles and design aspects of various DBMS and reporting concepts.
- Solid understanding of key DBMS platforms like SQL Server, Azure SQL
- Results-oriented, diligent, and works with a sense of urgency. Assertive, responsible for his/her own work (self-directed), have a strong affinity for defining work in deliverables, and be willing to commit to deadlines.
- Experience in MDM tools like MS DQ, SAS DM Studio, Tamr, Profisee, Reltio etc.
- Experience in Report and Dashboard development
- Statistical and Machine Learning models
- Python (sklearn, numpy, pandas, genism)
- Nice to Have:
- 1yr of ETL experience
- Natural Language Processing
- Neural networks and Deep learning
- xperience in keras,tensorflow,spacy, nltk, LightGBM python library
Interaction : Frequently interacts with subordinate supervisors.
Education : Bachelor’s degree, preferably in Computer Science, B.E or other quantitative field related to the area of assignment. Professional certification related to the area of assignment may be required
Experience : 7 years of Pharmaceutical /Biotech/life sciences experience, 5 years of Clinical Trials experience and knowledge, Excellent Documentation, Communication, and Presentation Skills including PowerPoint
We are looking for an engineer with ML/DL background.
Ideal candidate should have the following skillset
1) Python
2) Tensorflow
3) Experience building and deploying systems
4) Experience with Theano/Torch/Caffe/Keras all useful
5) Experience Data warehousing/storage/management would be a plus
6) Experience writing production software would be a plus
7) Ideal candidate should have developed their own DL architechtures apart from using open source architechtures.
8) Ideal candidate would have extensive experience with computer vision applications
Candidates would be responsible for building Deep Learning models to solve specific problems. Workflow would look as follows:
1) Define Problem Statement (input -> output)
2) Preprocess Data
3) Build DL model
4) Test on different datasets using Transfer Learning
5) Parameter Tuning
6) Deployment to production
Candidate should have experience working on Deep Learning with an engineering degree from a top tier institute (preferably IIT/BITS or equivalent)