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Role Summary

As a Data Engineer, you will be an integral part of our Data Engineering team supporting an event-driven server less data engineering pipeline on AWS cloud, responsible for assisting in the end-to-end analysis, development & maintenance of data pipelines and systems (DataOps). You will work closely with fellow data engineers & production support to ensure the availability and reliability of data for analytics and business intelligence purposes.

Requirements:

·      Around 4 years of working experience in data warehousing / BI system.

·      Strong hands-on experience with Snowflake AND strong programming skills in Python

·      Strong hands-on SQL skills

·      Knowledge with any of the cloud databases such as Snowflake,Redshift,Google BigQuery,RDS,etc.

·      Knowledge on debt for cloud databases

·      AWS Services such as SNS, SQS, ECS, Docker, Kinesis & Lambda functions

·      Solid understanding of ETL processes, and data warehousing concepts

·      Familiarity with version control systems (e.g., Git/bit bucket, etc.) and collaborative development practices in an agile framework

·      Experience with scrum methodologies

·      Infrastructure build tools such as CFT / Terraform is a plus.

·      Knowledge on Denodo, data cataloguing tools & data quality mechanisms is a plus.

·      Strong team player with good communication skills.

Overview Optisol Business Solutions

OptiSol was named on this year's Best Companies to Work for list by Great place to work. We are a team of about 500+ Agile employees with a development center in India and global offices in the US, UK (United Kingdom), Australia, Ireland, Sweden, and Dubai. 16+ years of joyful journey and we have built about 500+ digital solutions. We have 200+ happy and satisfied clients across 24 countries.

Benefits, working with Optisol

·      Great Learning & Development program

·      Flextime, Work-at-Home & Hybrid Options

·      A knowledgeable, high-achieving, experienced & fun team.

·      Spot Awards & Recognition.

·      The chance to be a part of next success story.

·      A competitive base salary.

More Than Just a Job, We Offer an Opportunity To Grow. Are you the one, who looks out to Build your Future & Build your Dream? We have the Job for you, to make your dream comes true.

Job Description:

1.Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges

a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem

b. Improve Model accuracy to deliver greater business impact

c.Estimate business impact due to deployment of model

2.Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge

3.Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines

4.Design , develop & deploy Deep learning models using Tensorflow / Pytorch 

5.Experience in using Deep learning models with text, speech, image and video data

a.Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc

b.Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV

c.Knowledge of State of the art Deep learning algorithms

6.Optimize and tune Deep Learnings model for best possible accuracy

7.Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau

8.Work with application teams, in deploying models on cloud as a service or on-prem

a.Deployment of models in Test / Control framework for tracking

b.Build CI/CD pipelines for ML model deployment

9.Integrating AI&ML models with other applications using REST APIs and other connector technologies

10.Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.

· Technology/Subject Matter Expertise

• Sufficient expertise in machine learning, mathematical and statistical sciences
• Use of versioning & Collaborative tools like Git / Github
• Good understanding of landscape of AI solutions – cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA Programming
• Develop prototype level ideas into a solution that can scale to industrial grade strength
• Ability to quantify & estimate the impact of ML models.

· Softskills Profile

• Curiosity to think in fresh and unique ways with the intent of breaking new ground.
• Must have the ability to share, explain and “sell” their thoughts, processes, ideas and opinions, even outside their own span of control
• Ability to think ahead, and anticipate the needs for solving the problem will be important

·        Ability to communicate key messages effectively, and articulate strong opinions in large forums

· Desirable Experience:

• Keen contributor to open source communities, and communities like Kaggle
• Ability to process Huge amount of Data using Pyspark/Hadoop
• Development & Application of Reinforcement Learning
• Knowledge of Optimization/Genetic Algorithms
• Operationalizing Deep learning model for a customer and understanding nuances of scaling such models in real scenarios
• Optimize and tune deep learning model for best possible accuracy
• Understanding of stream data processing, RPA, edge computing, AR/VR etc
• Appreciation of digital ethics, data privacy will be important
• Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus
• Experience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plus

Data Strategy and Planning:

Collaborate with stakeholders to develop and implement data management strategies aligned with business objectives.

Define data standards, policies, and procedures to ensure consistent and accurate data collection and storage.

Data Collection and Integration:

Identify and assess various data sources, both internal and external, to gather relevant and reliable data.

Design and implement data collection methods and processes to ensure data is captured efficiently.

Oversee data integration initiatives to consolidate data from different sources into a unified database.

Data Quality Assurance:

Develop and enforce data quality standards to ensure the accuracy, completeness, and consistency of data.

Implement data validation processes and routines to identify and rectify data discrepancies or errors.

Database Management:

Maintain and optimize data storage systems, including databases, data warehouses, and data lakes.

Ensure data security and compliance with relevant data protection regulations.

Data Analysis and Reporting:

Collaborate with analysts to provide clean and structured data for analysis.

Assist in creating data visualizations and reports to communicate insights and findings to stakeholders.

Team Collaboration:

Work closely with IT teams, data scientists, analysts, and other stakeholders to define data requirements and resolve technical issues.

Provide guidance and training to team members regarding data management best practices.

• Must have the experience of leading teams and drive customer interactions
• Must have multiple successful deployments user stories
• Extensive hands on experience in Apache Spark along with HiveQL
• Sound knowledge in Amazon Web Services or any other Cloud environment.
• Experienced in data flow orchestration using Apache Airflow
• JSON, XML, CSV, Parquet file formats with snappy compression.
• File movements between HDFS and AWS S3
• Experience in shell scripting and scripting to automate report generation and migration of reports to AWS S3
• Worked in building a data pipeline using Pandas and Flask FrameworkGood Familiarity with Anaconda and Jupyternotebook

We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve our company.
We will rely on you to build data products to extract valuable business insights.
In this role, you should be highly analytical with a knack for analysis, math and statistics.
Critical thinking and problem-solving skills are essential for interpreting data.
We also want to see a passion for machine-learning and research.
Your goal will be to help our company analyze trends to make better decisions.
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 SQL,Python,R,ggplot2, matplotlib, seaborn, Shiny, Dash; familiarity with Scala, Java or C++ is an asset
• Experience using business intelligence tools (e.g. Tableau) and data frameworks
• Analytical mind and business acumen
• Strong math skills in statistics, algebra
• Problem-solving aptitude
• Excellent communication and presentation skills
• BSc/BE in Computer Science, Engineering or relevant field;
• graduate degree in Data Science or other quantitative field is preferred