- Python coding skills
- Scikit-learn, pandas, tensorflow/keras experience
- Machine learning: designing ml models and explaining them for regression, classification, dimensionality reduction, anomaly detection etc
- Implementing Machine learning models and pushing it to production
- Creating docker images for ML models, REST API creation in Python
- Additional Skills Compulsory:
- Knowledge and professional experience of text and NLP related projects such as - text classification, text summarization, topic modeling etc
- Additional Skills Compulsory:
- Knowledge and professional experience of vision and deep learning for documents - CNNs, Deep neural networks using tensorflow for Keras for object detection, OCR implementation, document extraction etc
About MNC
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Lead Data Engineer
Data Engineers develop modern data architecture approaches to meet key business objectives and provide end-to-end data solutions. You might spend a few weeks with a new client on a deep technical review or a complete organizational review, helping them to understand the potential that data brings to solve their most pressing problems. On other projects, you might be acting as the architect, leading the design of technical solutions, or perhaps overseeing a program inception to build a new product. It could also be a software delivery project where you're equally happy coding and tech-leading the team to implement the solution.
Job responsibilities
· You might spend a few weeks with a new client on a deep technical review or a complete organizational review, helping them to understand the potential that data brings to solve their most pressing problems
· You will partner with teammates to create complex data processing pipelines in order to solve our clients' most ambitious challenges
· You will collaborate with Data Scientists in order to design scalable implementations of their models
· You will pair to write clean and iterative code based on TDD
· Leverage various continuous delivery practices to deploy, support and operate data pipelines
· Advise and educate clients on how to use different distributed storage and computing technologies from the plethora of options available
· Develop and operate modern data architecture approaches to meet key business objectives and provide end-to-end data solutions
· Create data models and speak to the tradeoffs of different modeling approaches
· On other projects, you might be acting as the architect, leading the design of technical solutions, or perhaps overseeing a program inception to build a new product
· Seamlessly incorporate data quality into your day-to-day work as well as into the delivery process
· Assure effective collaboration between Thoughtworks' and the client's teams, encouraging open communication and advocating for shared outcomes
Job qualifications Technical skills
· You are equally happy coding and leading a team to implement a solution
· You have a track record of innovation and expertise in Data Engineering
· You're passionate about craftsmanship and have applied your expertise across a range of industries and organizations
· You have a deep understanding of data modelling and experience with data engineering tools and platforms such as Kafka, Spark, and Hadoop
· You have built large-scale data pipelines and data-centric applications using any of the distributed storage platforms such as HDFS, S3, NoSQL databases (Hbase, Cassandra, etc.) and any of the distributed processing platforms like Hadoop, Spark, Hive, Oozie, and Airflow in a production setting
· Hands on experience in MapR, Cloudera, Hortonworks and/or cloud (AWS EMR, Azure HDInsights, Qubole etc.) based Hadoop distributions
· You are comfortable taking data-driven approaches and applying data security strategy to solve business problems
· You're genuinely excited about data infrastructure and operations with a familiarity working in cloud environments
· Working with data excites you: you have created Big data architecture, you can build and operate data pipelines, and maintain data storage, all within distributed systems
Professional skills
· Advocate your data engineering expertise to the broader tech community outside of Thoughtworks, speaking at conferences and acting as a mentor for more junior-level data engineers
· You're resilient and flexible in ambiguous situations and enjoy solving problems from technical and business perspectives
· An interest in coaching others, sharing your experience and knowledge with teammates
· You enjoy influencing others and always advocate for technical excellence while being open to change when needed
We are looking for an exceptionally talented Lead data engineer who has exposure in implementing AWS services to build data pipelines, api integration and designing data warehouse. Candidate with both hands-on and leadership capabilities will be ideal for this position.
Qualification: At least a bachelor’s degree in Science, Engineering, Applied Mathematics. Preferred Masters degree
Job Responsibilities:
• Total 6+ years of experience as a Data Engineer and 2+ years of experience in managing a team
• Have minimum 3 years of AWS Cloud experience.
• Well versed in languages such as Python, PySpark, SQL, NodeJS etc
• Has extensive experience in Spark ecosystem and has worked on both real time and batch processing
• Have experience in AWS Glue, EMR, DMS, Lambda, S3, DynamoDB, Step functions, Airflow, RDS, Aurora etc.
• Experience with modern Database systems such as Redshift, Presto, Hive etc.
• Worked on building data lakes in the past on S3 or Apache Hudi
• Solid understanding of Data Warehousing Concepts
• Good to have experience on tools such as Kafka or Kinesis
• Good to have AWS Developer Associate or Solutions Architect Associate Certification
• Have experience in managing a team
2. hands on experience using python, sql, tablaue
3. Data Analyst
About Amagi & Growth
Amagi Corporation is a next-generation media technology company that provides cloud broadcast and targeted advertising solutions to broadcast TV and streaming TV platforms. Amagi enables content owners to launch, distribute and monetize live linear channels on Free-Ad-Supported TV and video services platforms. Amagi also offers 24x7 cloud managed services bringing simplicity, advanced automation, and transparency to the entire broadcast operations. Overall, Amagi supports 500+ channels on its platform for linear channel creation, distribution, and monetization with deployments in over 40 countries. Amagi has offices in New York (Corporate office), Los Angeles, and London, broadcast operations in New Delhi, and our Development & Innovation center in Bangalore. Amagi is also expanding in Singapore, Canada and other countries.
Amagi has seen phenomenal growth as a global organization over the last 3 years. Amagi has been a profitable firm for the last 2 years, and is now looking at investing in multiple new areas. Amagi has been backed by 4 investors - Emerald, Premji Invest, Nadathur and Mayfield. As of the fiscal year ending March 31, 2021, the company witnessed stellar growth in the areas of channel creation, distribution, and monetization, enabling customers to extend distribution and earn advertising dollars while saving up to 40% in cost of operations compared to traditional delivery models. Some key highlights of this include:
· Annual revenue growth of 136%
· 44% increase in customers
· 50+ Free Ad Supported Streaming TV (FAST) platform partnerships and 100+ platform partnerships globally
· 250+ channels added to its cloud platform taking the overall tally to more than 500
· Approximately 2 billion ad opportunities every month supporting OTT ad-insertion for 1000+ channels
· 60% increase in workforce in the US, UK, and India to support strong customer growth (current headcount being 360 full-time employees + Contractors)
· 5-10x growth in ad impressions among top customers
Work Timing: 5 Days A Week
Responsibilities include:
• Ensure right stakeholders gets right information at right time
• Requirement gathering with stakeholders to understand their data requirement
• Creating and deploying reports
• Participate actively in datamarts design discussions
• Work on both RDBMS as well as Big Data for designing BI Solutions
• Write code (queries/procedures) in SQL / Hive / Drill that is both functional and elegant,
following appropriate design patterns
• Design and plan BI solutions to automate regular reporting
• Debugging, monitoring and troubleshooting BI solutions
• Creating and deploying datamarts
• Writing relational and multidimensional database queries
• Integrate heterogeneous data sources into BI solutions
• Ensure Data Integrity of data flowing from heterogeneous data sources into BI solutions.
Minimum Job Qualifications:
• BE/B.Tech in Computer Science/IT from Top Colleges
• 1-5 years of experience in Datawarehousing and SQL
• Excellent Analytical Knowledge
• Excellent technical as well as communication skills
• Attention to even the smallest detail is mandatory
• Knowledge of SQL query writing and performance tuning
• Knowledge of Big Data technologies like Apache Hadoop, Apache Hive, Apache Drill
• Knowledge of fundamentals of Business Intelligence
• In-depth knowledge of RDBMS systems, Datawarehousing and Datamarts
• Smart, motivated and team oriented
Desirable Requirements
• Sound knowledge of software development in Programming (preferably Java )
• Knowledge of the software development lifecycle (SDLC) and models
We’re building the future of private financial markets
Traditionally a space only for the wealthy and well-connected, we believe in a future where private markets are more accessible to investors and fundraisers. By leveling the playing field we hope to create a more equitable economy, where inspiring companies are connected to inspired investors, whoever and wherever they are.
Leveraging our trusted brand, global networks and incredible team, we’re building a technology-enabled ecosystem that is as diverse and dynamic as our investor network. As we progress on this ambitious journey, we’re looking for energetic and creative people to support and leave their mark on our platform.
Before Applying
- We have big plans to disrupt the traditional fundraising process for private businesses
- You will work with a diverse team of former investment bankers, strategy consultants and business owners in developing, monitoring, and improving products to facilitate the activity of private investing
- Everything we do is focused on helping build the private capital markets for the next generation of business owners and investors
- We work really hard but play really hard as well
Job purpose
- We are looking for passionate Data Scientists with strong problem-solving skills and prior experience in building machine learning models. You should possess the ability to thrive in a fast-paced environment. As a Data Scientist, working with passionate data-driven enthusiasts, you will lead the deployment of decision sciences with advanced analytics as well as machine learning and AI capabilities to support various lines of businesses. You will also help to enable a data driven culture within the organization.
Roles and responsibilities
- Work with other Data Scientists, Data Engineers, Data Analysts, Software engineers to build and manage data products
- Work on cross-functional projects using advanced data modeling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities.
- Develop an enterprise data science strategy to achieve scale, synergies, and sustainability of model deployment
- Undertake rigorous analyses of business problems on structured and unstructured data with advanced quantitative techniques.
- Apply your expertise in data science, statistical analysis, data mining and the visualisation of data to derive insights that value-add to business decision making (e.g. hypothesis testing, development of MVPs, prototyping etc).
- Manage and optimize processes for data intake, validation, mining, and engineering as well as modeling, visualization and communication deliverable.
You’ll be a great fit for us if you
- Bachelor or Master’s in Computer Science, Statistics, Mathematics, Economics, or any other related fields
- At least 3 to 5 years of hands-on experience in a Data Science role with exposure and proficiency in quantitative and statistical analysis, predictive analytics,multi-variate testing and algorithm-optimization for machine learning
- Deep expertise in a range of ML concepts, frameworks and techniques such as logistic regression, clustering, dimensional reduction, recommendation systems,neural nets etc.
- Strong understanding of data infrastructure technologies (e.g. Spark, TensorFlow etc).
- Familiarity with data engineering methodologies, including SQL, ETL and experience in manipulating data sets with structured and unstructured data using Hadoop, AWS or other big data platforms.
- Highly proficient in data visualization and the use of dash boarding tools (e.g.Tableau, Matplotlib, plot.ly etc).
- Proven track record in delivering bespoke data science solutions in a cross-functional setting.
- Experience in managing a small team is preferred.
Bonus attributes
- Interested in dealing with data, including finding, and exploring more efficient ways/programs (e.g. machine learning) to collect, store, and analyse data
- Preferably have some understanding of terms in financial statements and financial ratios
- Strong problem-solving skills – able to find various ways to solve problems and decide which solution to move forward
- Ability to work under pressure and tight timings
- Team oriented, but highly independent for their own projects
- High level of organisational skills and ability to prioritize
2. Should understand the importance and know-how of taking the machine-learning-based solution to the consumer.
3. Hands-on experience with statistical, machine-learning tools and techniques
4. Good exposure to Deep learning libraries like Tensorflow, PyTorch.
5. Experience in implementing Deep Learning techniques, Computer Vision and NLP. The candidate should be able to develop the solution from scratch with Github codes exposed.
6. Should be able to read research papers and pick ideas to quickly reproduce research in the most comfortable Deep Learning library.
7. Should be strong in data structures and algorithms. Should be able to do code complexity analysis/optimization for smooth delivery to production.
8. Expert level coding experience in Python.
9. Technologies: Backend - Python (Programming Language)
10. Should have the ability to think long term solutions, modularity, and reusability of the components.
11. Should be able to work in a collaborative way. Should be open to learning from peers as well as constantly bring new ideas to the table.
12. Self-driven missile. Open to peer criticism, feedback and should be able to take it positively. Ready to be held accountable for the responsibilities undertaken.