Job Description
Want to make every line of code count? Tired of being a small cog in a big machine? Like a fast-paced environment where stuff get DONE? Wanna grow with a fast-growing company (both career and compensation)? Like to wear different hats? Join ThinkDeeply in our mission to create and apply Enterprise-Grade AI for all types of applications.
Seeking an M.L. Engineer with high aptitude toward development. Will also consider coders with high aptitude in M.L. Years of experience is important but we are also looking for interest and aptitude. As part of the early engineering team, you will have a chance to make a measurable impact in future of Thinkdeeply as well as having a significant amount of responsibility.
Experience
10+ Years
Location
Bozeman/Hyderabad
Skills
Required Skills:
Bachelors/Masters or Phd in Computer Science or related industry experience
3+ years of Industry Experience in Deep Learning Frameworks in PyTorch or TensorFlow
7+ Years of industry experience in scripting languages such as Python, R.
7+ years in software development doing at least some level of Researching / POCs, Prototyping, Productizing, Process improvement, Large-data processing / performance computing
Familiar with non-neural network methods such as Bayesian, SVM, Adaboost, Random Forests etc
Some experience in setting up large scale training data pipelines.
Some experience in using Cloud services such as AWS, GCP, Azure
Desired Skills:
Experience in building deep learning models for Computer Vision and Natural Language Processing domains
Experience in productionizing/serving machine learning in industry setting
Understand the principles of developing cloud native applications
Responsibilities
Collect, Organize and Process data pipelines for developing ML models
Research and develop novel prototypes for customers
Train, implement and evaluate shippable machine learning models
Deploy and iterate improvements of ML Models through feedback
About Thinkdeeply
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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.
Airflow developer:
Exp: 5 to 10yrs & Relevant exp must be above 4 Years.
Work location: Hyderabad (Hybrid Model)
Job description:
· Experience in working on Airflow.
· Experience in SQL, Python, and Object-oriented programming.
· Experience in the data warehouse, database concepts, and ETL tools (Informatica, DataStage, Pentaho, etc.).
· Azure experience and exposure to Kubernetes.
· Experience in Azure data factory, Azure Databricks, and Snowflake.
Required Skills: Azure Databricks/Data Factory, Kubernetes/Dockers, DAG Development, Hands-on Python coding.
Role : Sr Data Scientist / Tech Lead – Data Science
Number of positions : 8
Responsibilities
- Lead a team of data scientists, machine learning engineers and big data specialists
- Be the main point of contact for the customers
- Lead data mining and collection procedures
- Ensure data quality and integrity
- Interpret and analyze data problems
- Conceive, plan and prioritize data projects
- Build analytic systems and predictive models
- Test performance of data-driven products
- Visualize data and create reports
- Experiment with new models and techniques
- Align data projects with organizational goals
Requirements (please read carefully)
- Very strong in statistics fundamentals. Not all data is Big Data. The candidate should be able to derive statistical insights from very few data points if required, using traditional statistical methods.
- Msc-Statistics/ Phd.Statistics
- Education – no bar, but preferably from a Statistics academic background (eg MSc-Stats, MSc-Econometrics etc), given the first point
- Strong expertise in Python (any other statistical languages/tools like R, SAS, SPSS etc are just optional, but Python is absolutely essential). If the person is very strong in Python, but has almost nil knowledge in the other statistical tools, he/she will still be considered a good candidate for this role.
- Proven experience as a Data Scientist or similar role, for about 7-8 years
- Solid understanding of machine learning and AI concepts, especially wrt choice of apt candidate algorithms for a use case, and model evaluation.
- Good expertise in writing SQL queries (should not be dependent upon anyone else for pulling in data, joining them, data wrangling etc)
- Knowledge of data management and visualization techniques --- more from a Data Science perspective.
- Should be able to grasp business problems, ask the right questions to better understand the problem breadthwise /depthwise, design apt solutions, and explain that to the business stakeholders.
- Again, the last point above is extremely important --- should be able to identify solutions that can be explained to stakeholders, and furthermore, be able to present them in simple, direct language.
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Position: ETL Developer
Location: Mumbai
Exp.Level: 4+ Yrs
Required Skills:
* Strong scripting knowledge such as: Python and Shell
* Strong relational database skills especially with DB2/Sybase
* Create high quality and optimized stored procedures and queries
* Strong with scripting language such as Python and Unix / K-Shell
* Strong knowledge base of relational database performance and tuning such as: proper use of indices, database statistics/reorgs, de-normalization concepts.
* Familiar with lifecycle of a trade and flows of data in an investment banking operation is a plus.
* Experienced in Agile development process
* Java Knowledge is a big plus but not essential
* Experience in delivery of metrics / reporting in an enterprise environment (e.g. demonstrated experience in BI tools such as Business Objects, Tableau, report design & delivery) is a plus
* Experience on ETL processes and tools such as Informatica is a plus. Real time message processing experience is a big plus.
* Good team player; Integrity & ownership
- Cloud: GCP
- Must have: BigQuery, Python, Vertex AI
- Nice to have Services: Data Plex
- Exp level: 5-10 years.
- Preferred Industry (nice to have): Manufacturing – B2B sales
- Analyze and organize raw data
- Build data systems and pipelines
- Evaluate business needs and objectives
- Interpret trends and patterns
- Conduct complex data analysis and report on results
- Build algorithms and prototypes
- Combine raw information from different sources
- Explore ways to enhance data quality and reliability
- Identify opportunities for data acquisition
- Should have experience in Python, Django Micro Service Senior developer with Financial Services/Investment Banking background.
- Develop analytical tools and programs
- Collaborate with data scientists and architects on several projects
- Should have 5+ years of experience as a data engineer or in a similar role
- Technical expertise with data models, data mining, and segmentation techniques
- Should have experience programming languages such as Python
- Hands-on experience with SQL database design
- Great numerical and analytical skills
- Degree in Computer Science, IT, or similar field; a Master’s is a plus
- Data engineering certification (e.g. IBM Certified Data Engineer) is a plus
Tiger Analytics is a global AI & analytics consulting firm. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modeled around expertise and mutual respect with a team first mindset. Working at Tiger, you’ll be at the heart of this AI revolution. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire.
We are headquartered in the Silicon Valley and have our delivery centres across the globe. The below role is for our Chennai or Bangalore office, or you can choose to work remotely.
About the Role:
As an Associate Director - Data Science at Tiger Analytics, you will lead data science aspects of endto-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction.
• Work closely with internal teams and client stakeholders to design analytical approaches to
solve business problems
• Develop and enhance a broad range of cutting-edge data analytics and machine learning
problems across a variety of industries.
• Work on various aspects of the ML ecosystem – model building, ML pipelines, logging &
versioning, documentation, scaling, deployment, monitoring and maintenance etc.
• Lead a team of data scientists and engineers to embed AI and analytics into the client
business decision processes.
Desired Skills:
• High level of proficiency in a structured programming language, e.g. Python, R.
• Experience designing data science solutions to business problems
• Deep understanding of ML algorithms for common use cases in both structured and
unstructured data ecosystems.
• Comfortable with large scale data processing and distributed computing
• Excellent written and verbal communication skills
• 10+ years exp of which 8 years of relevant data science experience including hands-on
programming.
Designation will be commensurate with expertise/experience. Compensation packages among the best in the industry.
Intro
Our data and risk team is the core pillar of our business that harnesses alternative data sources to guide the decisions we make at Rely. The team designs, architects, as well as develop and maintain a scalable data platform the powers our machine learning models. Be part of a team that will help millions of consumers across Asia, to be effortlessly in control of their spending and make better decisions.
What will you do
The data engineer is focused on making data correct and accessible, and building scalable systems to access/process it. Another major responsibility is helping AI/ML Engineers write better code.
• Optimize and automate ingestion processes for a variety of data sources such as: click stream, transactional and many other sources.
- Create and maintain optimal data pipeline architecture and ETL processes
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Develop data pipeline and infrastructure to support real-time decisions
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data' technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs.
What will you need
• 2+ hands-on experience building and implementation of large scale production pipeline and Data Warehouse
• Experience dealing with large scale
- Proficiency in writing and debugging complex SQLs
- Experience working with AWS big data tools
• Ability to lead the project and implement best data practises and technology
Data Pipelining
- Strong command in building & optimizing data pipelines, architectures and data sets
- Strong command on relational SQL & noSQL databases including Postgres
- Data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
Big Data: Strong experience in big data tools & applications
- Tools: Hadoop, Spark, HDFS etc
- AWS cloud services: EC2, EMR, RDS, Redshift
- Stream-processing systems: Storm, Spark-Streaming, Flink etc.
- Message queuing: RabbitMQ, Spark etc
Software Development & Debugging
- Strong experience in object-oriented programming/object function scripting languages: Python, Java, C++, Scala, etc
- Strong hold on data structures & algorithms
What would be a bonus
- Prior experience working in a fast-growth Startup
- Prior experience in the payments, fraud, lending, advertising companies dealing with large scale data