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About antuit.ai

Antuit.ai is the leader in AI-powered SaaS solutions for Demand Forecasting & Planning, Merchandising and Pricing. We have the industry’s first solution portfolio – powered by Artificial Intelligence and Machine Learning – that can help you digitally transform your Forecasting, Assortment, Pricing, and Personalization solutions. World-class retailers and consumer goods manufacturers leverage antuit.ai solutions, at scale, to drive outsized business results globally with higher sales, margin and sell-through.

Antuit.ai’s executives, comprised of industry leaders from McKinsey, Accenture, IBM, and SAS, and our team of Ph.Ds., data scientists, technologists, and domain experts, are passionate about delivering real value to our clients. Antuit.ai is funded by Goldman Sachs and Zodius Capital.

The Role:

Antuit.ai is interested in hiring a Principal Data Scientist, this person will facilitate standing up standardization and automation ecosystem for ML product delivery, he will also actively participate in managing implementation, design and tuning of product to meet business needs.

Responsibilities:

Responsibilities includes, but are not limited to the following:

• Manage and provides technical expertise to the delivery team. This includes recommendation of solution alternatives, identification of risks and managing business expectations.
• Design, build reliable and scalable automated processes for large scale machine learning.
• Use engineering expertise to help design solutions to novel problems in software development, data engineering, and machine learning. 
• Collaborate with Business, Technology and Product teams to stand-up MLOps process.
• Apply your experience in making intelligent, forward-thinking, technical decisions to delivery ML ecosystem, including implementing new standards, architecture design, and workflows tools.
• Deep dive into complex algorithmic and product issues in production
• Own metrics and reporting for delivery team. 
• Set a clear vision for the team members and working cohesively to attain it.
• Mentor and coach team members

Qualifications and Skills:

Requirements

• Engineering degree in any stream
• Has at least 7 years of prior experience in building ML driven products/solutions
• Excellent programming skills in any one of the language C++ or Python or Java.
• Hands on experience on open source libraries and frameworks- Tensorflow,Pytorch, MLFlow, KubeFlow, etc.
• Developed and productized large-scale models/algorithms in prior experience
• Can drive fast prototypes/proof of concept in evaluating various technology, frameworks/performance benchmarks.
• Familiar with software development practices/pipelines (DevOps- Kubernetes, docker containers, CI/CD tools).
• Good verbal, written and presentation skills.
• Ability to learn new skills and technologies.
• 3+ years working with retail or CPG preferred.
• Experience in forecasting and optimization problems, particularly in the CPG / Retail industry preferred.

Information Security Responsibilities

• Understand and adhere to Information Security policies, guidelines and procedure, practice them for protection of organizational data and Information System.
• Take part in Information Security training and act accordingly while handling information.
• Report all suspected security and policy breach to Infosec team or appropriate authority (CISO).

EEOC

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

1. Big data developer with 8+ years of professional IT experience with expertise in Hadoop ecosystem components in ingestion, Data modeling, querying, processing, storage, analysis, Data Integration and Implementing enterprise level systems spanning Big Data.
2. A skilled developer with strong problem solving, debugging and analytical capabilities, who actively engages in understanding customer requirements.
3. Expertise in Apache Hadoop ecosystem components like Spark, Hadoop Distributed File Systems(HDFS), HiveMapReduce, Hive, Sqoop, HBase, Zookeeper, YARN, Flume, Pig, Nifi, Scala and Oozie.
4. Hands on experience in creating real - time data streaming solutions using Apache Spark core, Spark SQL & DataFrames, Kafka, Spark streaming and Apache Storm.
5. Excellent knowledge of Hadoop architecture and daemons of Hadoop clusters, which include Name node,Data node, Resource manager, Node Manager and Job history server.
6. Worked on both Cloudera and Horton works in Hadoop Distributions. Experience in managing Hadoop clustersusing Cloudera Manager tool.
7. Well versed in installation, Configuration, Managing of Big Data and underlying infrastructure of Hadoop Cluster.
8. Hands on experience in coding MapReduce/Yarn Programs using Java, Scala and Python for analyzing Big Data.
9. Exposure to Cloudera development environment and management using Cloudera Manager.
10. Extensively worked on Spark using Scala on cluster for computational (analytics), installed it on top of Hadoop performed advanced analytical application by making use of Spark with Hive and SQL/Oracle .
11. Implemented Spark using PYTHON and utilizing Data frames and Spark SQL API for faster processing of data and handled importing data from different data sources into HDFS using Sqoop and performing transformations using Hive, MapReduce and then loading data into HDFS.
12. Used Spark Data Frames API over Cloudera platform to perform analytics on Hive data.
13. Hands on experience in MLlib from Spark which are used for predictive intelligence, customer segmentation and for smooth maintenance in Spark streaming.
14. Experience in using Flume to load log files into HDFS and Oozie for workflow design and scheduling.
15. Experience in optimizing MapReduce jobs to use HDFS efficiently by using various compression mechanisms.
16. Working on creating data pipeline for different events of ingestion, aggregation, and load consumer response data into Hive external tables in HDFS location to serve as feed for tableau dashboards.
17. Hands on experience in using Sqoop to import data into HDFS from RDBMS and vice-versa.
18. In-depth Understanding of Oozie to schedule all Hive/Sqoop/HBase jobs.
19. Hands on expertise in real time analytics with Apache Spark.
20. Experience in converting Hive/SQL queries into RDD transformations using Apache Spark, Scala and Python.
21. Extensive experience in working with different ETL tool environments like SSIS, Informatica and reporting tool environments like SQL Server Reporting Services (SSRS).
22. Experience in Microsoft cloud and setting cluster in Amazon EC2 & S3 including the automation of setting & extending the clusters in AWS Amazon cloud.
23. Extensively worked on Spark using Python on cluster for computational (analytics), installed it on top of Hadoop performed advanced analytical application by making use of Spark with Hive and SQL.
24. Strong experience and knowledge of real time data analytics using Spark Streaming, Kafka and Flume.
25. Knowledge in installation, configuration, supporting and managing Hadoop Clusters using Apache, Cloudera (CDH3, CDH4) distributions and on Amazon web services (AWS).
26. Experienced in writing Ad Hoc queries using Cloudera Impala, also used Impala analytical functions.
27. Experience in creating Data frames using PySpark and performing operation on the Data frames using Python.
28. In depth understanding/knowledge of Hadoop Architecture and various components such as HDFS and MapReduce Programming Paradigm, High Availability and YARN architecture.
29. Establishing multiple connections to different Redshift clusters (Bank Prod, Card Prod, SBBDA Cluster) and provide the access for pulling the information we need for analysis. 
30. Generated various kinds of knowledge reports using Power BI based on Business specification. 
31. Developed interactive Tableau dashboards to provide a clear understanding of industry specific KPIs using quick filters and parameters to handle them more efficiently.
32. Well Experience in projects using JIRA, Testing, Maven and Jenkins build tools.
33. Experienced in designing, built, and deploying and utilizing almost all the AWS stack (Including EC2, S3,), focusing on high-availability, fault tolerance, and auto-scaling.
34. Good experience with use-case development, with Software methodologies like Agile and Waterfall.
35. Working knowledge of Amazon's Elastic Cloud Compute( EC2 ) infrastructure for computational tasks and Simple Storage Service ( S3 ) as Storage mechanism.
36. Good working experience in importing data using Sqoop, SFTP from various sources like RDMS, Teradata, Mainframes, Oracle, Netezza to HDFS and performed transformations on it using Hive, Pig and Spark .
37. Extensive experience in Text Analytics, developing different Statistical Machine Learning solutions to various business problems and generating data visualizations using Python and R.
38. Proficient in NoSQL databases including HBase, Cassandra, MongoDB and its integration with Hadoop cluster.
39. Hands on experience in Hadoop Big data technology working on MapReduce, Pig, Hive as Analysis tool, Sqoop and Flume data import/export tools.

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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About Us :

Docsumo is Document AI software that helps enterprises capture data and analyze customer documents. We convert documents such as invoices, ID cards, and bank statements into actionable data. We are work with clients such as PayU, Arbor and Hitachi and backed by Sequoia, Barclays, Techstars, and Better Capital.

As a Senior Machine Learning you will be working directly with the CTO to develop end to end API products for the US market in the information extraction domain.

Responsibilities :

• You will be designing and building systems that help Docsumo process visual data i.e. as PDF & images of documents.
• You'll work in our Machine Intelligence team, a close-knit group of scientists and engineers who incubate new capabilities from whiteboard sketches all the way to finished apps.
• You will get to learn the ins and outs of building core capabilities & API products that can scale globally.
• Should have hands-on experience applying advanced statistical learning techniques to different types of data.
• Should be able to design, build and work with RESTful Web Services in JSON and XML formats. (Flask preferred)
• Should follow Agile principles and processes including (but not limited to) standup meetings, sprints and retrospectives.

Skills / Requirements :

• Minimum 3+ years experience working in machine learning, text processing, data science, information retrieval, deep learning, natural language processing, text mining, regression, classification, etc.
• Must have a full-time degree in Computer Science or similar (Statistics/Mathematics)
• Working with OpenCV, TensorFlow and Keras
• Working with Python: Numpy, Scikit-learn, Matplotlib, Panda
• Familiarity with Version Control tools such as Git
• Theoretical and practical knowledge of SQL / NoSQL databases with hands-on experience in at least one database system.
• Must be self-motivated, flexible, collaborative, with an eagerness to learn

4-6 years of total experience in data warehousing and business intelligence

3+ years of solid Power BI experience (Power Query, M-Query, DAX, Aggregates)

2 years’ experience building Power BI using cloud data (Snowflake, Azure Synapse, SQL DB, data lake)

Strong experience building visually appealing UI/UX in Power BI

Understand how to design Power BI solutions for performance (composite models, incremental refresh, analysis services)

Experience building Power BI using large data in direct query mode

Expert SQL background (query building, stored procedure, optimizing performance)