Data Engineer

Responsibilities

Researches, develops and maintains machine learning and statistical models for

business requirements

Work across the spectrum of statistical modelling including supervised,

unsupervised, & deep learning techniques to apply the right level of solution to

the right problem Coordinate with different functional teams to monitor outcomes and refine/

improve the machine learning models Implements models to uncover patterns and predictions creating business value and innovation

Identify unexplored data opportunities for the business to unlock and maximize

the potential of digital data within the organization

Develop NLP concepts and algorithms to classify and summarize structured/unstructured text data

Qualifications

3+ years of experience solving complex business problems using machine

learning.

Fluency in programming languages such as Python, NLP and Bert, is a must

Strong analytical and critical thinking skills

Experience in building production quality models using state-of-the-art technologies 

Familiarity with databases .

desirable Ability to collaborate on projects and work independently when required.

Previous experience in Fintech/payments domain is a bonus

You should have Bachelor’s or Master’s degree in Computer Science, Statistics

or Mathematics or another quantitative field from a top tier Institute

You will be responsible for designing, building, and maintaining data pipelines that handle Real-world data at Compile. You will be handling both inbound and outbound data deliveries at Compile for datasets including Claims, Remittances, EHR, SDOH, etc.

You will

• Work on building and maintaining data pipelines (specifically RWD).
• Build, enhance and maintain existing pipelines in pyspark, python and help build analytical insights and datasets.
• Scheduling and maintaining pipeline jobs for RWD.
• Develop, test, and implement data solutions based on the design.
• Design and implement quality checks on existing and new data pipelines.
• Ensure adherence to security and compliance that is required for the products.
• Maintain relationships with various data vendors and track changes and issues across vendors and deliveries.

You have

• Hands-on experience with ETL process (min of 5 years).
• Excellent communication skills and ability to work with multiple vendors.
• High proficiency with Spark, SQL.
• Proficiency in Data modeling, validation, quality check, and data engineering concepts.
• Experience in working with big-data processing technologies using - databricks, dbt, S3, Delta lake, Deequ, Griffin, Snowflake, BigQuery.
• Familiarity with version control technologies, and CI/CD systems.
• Understanding of scheduling tools like Airflow/Prefect.
• Min of 3 years of experience managing data warehouses.
• Familiarity with healthcare datasets is a plus.

Compile embraces diversity and equal opportunity in a serious way. We are committed to building a team of people from many backgrounds, perspectives, and skills. We know the more inclusive we are, the better our work will be.         

Job Description

1. Solid technical skills with a proven and successful history working with data at scale and empowering organizations through data
2. Big data processing frameworks: Spark, Scala, Hadoop, Hive, Kafka, EMR with Python
3. Advanced experience and hands-on architecture and administration experience on big data platforms

We are establishing infrastructure for internal and external reporting using Tableau and are looking for someone with experience building visualizations and dashboards in Tableau and using Tableau Server to deliver them to internal and external users. 

Required Experience 

• Implementation of interactive visualizations using Tableau Desktop  
• Integration with Tableau Server and support of production dashboards and embedded reports with it 

• Writing and optimization of SQL queries  
• Proficient in Python including the use of Pandas and numpy libraries to perform data exploration and analysis 
• 3  years of experience working as a Software Engineer / Senior Software Engineer 
• Bachelors in Engineering – can be Electronic and comm , Computer , IT  
• Well versed with Basic Data Structures Algorithms and system design 

• Should be capable of working well in a team – and should possess very good communication skills 
• Self-motivated and fun to work with and organized 
• Productive and efficient working remotely 
• Test driven mindset with a knack for finding issues and problems at earlier stages of development 
• Interest in learning and picking up a wide range of cutting edge technologies 

• Should be curious and interested in learning some Data science related concepts and domain knowledge 
• Work alongside other engineers on the team to elevate technology and consistently apply best practices 

Highly Desirable 

• Data Analytics 

• Experience in AWS cloud or any cloud technologies 
• Experience in BigData technologies and streaming like – pyspark, kafka is a big plus 
• Shell scripting  
• Preferred tech stack – Python, Rest API, Microservices, Flask/Fast API, pandas, numpy, linux, shell scripting, Airflow, pyspark 
• Has a strong backend experience – and worked with Microservices and Rest API’s - Flask, FastAPI, Databases Relational and Non-relational 

What you need to have:

Responsibilities Description:

Responsible for the development and implementation of machine learning algorithms and techniques to solve business problems and optimize member experiences. Primary duties may include are but not limited to: Design machine learning projects to address specific business problems determined by consultation with business partners. Work with data-sets of varying degrees of size and complexity including both structured and unstructured data. Piping and processing massive data-streams in distributed computing environments such as Hadoop to facilitate analysis. Implements batch and real-time model scoring to drive actions. Develops machine learning algorithms to build customized solutions that go beyond standard industry tools and lead to innovative solutions. Develop sophisticated visualization of analysis output for business users.

Experience Requirements:

BS/MA/MS/PhD in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics or related Quantitative disciplines. 2-4 years of experience in predictive analytics and advanced expertise with software such as Python, or any combination of education and experience which would provide an equivalent background. Experience in the healthcare sector. Experience in Deep Learning strongly preferred.

Required Technical Skill Set:

• Full cycle of building machine learning solutions,

o   Understanding of wide range of algorithms and their corresponding problems to solve

o   Data preparation and analysis

o   Model training and validation

o   Model application to the problem

• Experience using the full open source programming tools and utilities
• Experience in working in end-to-end data science project implementation.
• 2+ years of experience with development and deployment of Machine Learning applications
• 2+ years of experience with NLP approaches in a production setting
• Experience in building models using bagging and boosting algorithms
• Exposure/experience in building Deep Learning models for NLP/Computer Vision use cases preferred
• Ability to write efficient code with good understanding of core Data Structures/algorithms is critical
• Strong python skills following software engineering best practices
• Experience in using code versioning tools like GIT, bit bucket
• Experience in working in Agile projects
• Comfort & familiarity with SQL and Hadoop ecosystem of tools including spark
• Experience managing big data with efficient query program good to have
• Good to have experience in training ML models in tools like Sage Maker, Kubeflow etc.
• Good to have experience in frameworks to depict interpretability of models using libraries like Lime, Shap etc.
• Experience with Health care sector is preferred
• MS/M.Tech or PhD is a plus

• Use data to develop machine learning models that optimize decision making in Credit Risk, Fraud, Marketing, and Operations
• Implement data pipelines, new features, and algorithms that are critical to our production models
• Create scalable strategies to deploy and execute your models
• Write well designed, testable, efficient code
• Identify valuable data sources and automate collection processes.
• Undertake to preprocess of structured and unstructured data.
• Analyze large amounts of information to discover trends and patterns.

Requirements:

• 1+ years of experience in applied data science or engineering with a focus on machine learning
• Python expertise with good knowledge of machine learning libraries, tools, techniques, and frameworks (e.g. pandas, sklearn, xgboost, lightgbm, logistic regression, random forest classifier, gradient boosting regressor etc)
• strong quantitative and programming skills with a product-driven sensibility

Job Overview

                         We are looking for a ML Architect to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. They must have strong experience using variety of data mining and data analysis methods, building and implementing models, using/creating algorithm’s and creating/running simulations.  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. Automating to identify the textual data with their properties and structure form various type of document.

Responsibilities

• Selecting features, building and optimizing classifiers using machine learning techniques
• Data mining using state-of-the-art methods
• Enhancing data collection procedures to include information that is relevant for building analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis
• Creating automated anomaly detection systems and constant tracking of its performance
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Secure and manage when needed GPU cluster resources for events
• Write comprehensive internal feedback reports and find opportunities for improvements
• Manage GPU instances/machines to increase the performance and efficiency of the ML/DL model.

Skills and Qualifications

• Strong Hands-on experience in Python Programming
• Working experience with Computer Vision models - Object Detection Model, Image Classification
• Good experience in feature extraction, feature selection techniques and transfer learning
• Working Experience in building deep learning NLP Models for text classification, image analytics-CNN,RNN,LSTM.
• Working Experience in any of the AWS/GCP cloud platforms, exposure in fetching data from various sources.
• Good experience in exploratory data analysis, data visualisation, and other data preprocessing techniques.
• Knowledge in any one of the DL frameworks like Tensorflow, Pytorch, Keras, Caffe
• Good knowledge in statistics,distribution of data and in supervised and unsupervised machine learning algorithms.
• Exposure to OpenCV Familiarity with GPUs + CUDA
• Experience with NVIDIA software for cluster management and provisioning such as nvsm, dcgm and DeepOps.
• We are looking for a candidate with 14+ years of experience, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with AWS cloud services: EC2, RDS, AWS-Sagemaker(Added advantage)
• Experience with object-oriented/object function scripting languages in any: Python, Java, C++, Scala, etc.