Data Scientist

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

> Selecting features, building and optimizing classifiers using machine

> learning techniques

> Data mining using state-of-the-art methods

> Extending company’s data with third party sources of information when

> needed

> 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

> Doing ad-hoc analysis and presenting results in a clear manner

> Creating automated anomaly detection systems and constant tracking of

> its performance

Key Skills

> Hands-on experience of analysis tools like R, Advance Python

> Must Have Knowledge of statistical techniques and machine learning

> algorithms

> Artificial Intelligence

> Understanding of Text analysis- Natural Language processing (NLP)

> Knowledge on Google Cloud Platform

> Advanced Excel, PowerPoint skills

> Advanced communication (written and oral) and strong interpersonal

> skills

> Ability to work cross-culturally

> Good to have Deep Learning

> VBA and visualization tools like Tableau, PowerBI, Qliksense, Qlikview

> will be an added advantage

• Core Java: advanced level competency, should have worked on projects with core Java development.

• Linux shell : advanced level competency, work experience with Linux shell scripting, knowledge and experience to use important shell commands

• Rdbms, SQL: advanced level competency, Should have expertise in SQL query language syntax, should be well versed with aggregations, joins of SQL query language.

• Data structures and problem solving: should have ability to use appropriate data structure.

• AWS cloud : Good to have experience with aws serverless toolset along with aws infra

• Data Engineering ecosystem : Good to have experience and knowledge of data engineering, ETL, data warehouse (any toolset)

• Hadoop, HDFS, YARN : Should have introduction to internal working of these toolsets

• HIVE, MapReduce, Spark: Good to have experience developing transformations using hive queries, MapReduce job implementation and Spark Job Implementation. Spark implementation in Scala will be plus point.

• Airflow, Oozie, Sqoop, Zookeeper, Kafka: Good to have knowledge about purpose and working of these technology toolsets. Working experience will be a plus point here.

Senior Data Engineer

Responsibilities:

●      Clean, prepare and optimize data at scale for ingestion and consumption by machine learning models

●      Drive the implementation of new data management projects and re-structure of the current data architecture

●      Implement complex automated workflows and routines using workflow scheduling tools 

●      Build continuous integration, test-driven development and production deployment frameworks

●      Drive collaborative reviews of design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards 

●      Anticipate, identify and solve issues concerning data management to improve data quality

●      Design and build reusable components, frameworks and libraries at scale to support machine learning products 

●      Design and implement product features in collaboration with business and Technology stakeholders 

●      Analyze and profile data for the purpose of designing scalable solutions 

●      Troubleshoot complex data issues and perform root cause analysis to proactively resolve product and operational issues

●      Mentor and develop other data engineers in adopting best practices 

●      Able to influence and communicate effectively, both verbally and written, with team members and business stakeholders

Qualifications:

●      8+ years of experience developing scalable Big Data applications or solutions on distributed platforms

●      Experience in Google Cloud Platform (GCP) and good to have other cloud platform tools

●      Experience working with Data warehousing tools, including DynamoDB, SQL, and Snowflake

●      Experience architecting data products in Streaming, Serverless and Microservices Architecture and platform.

●      Experience with Spark (Scala/Python/Java) and Kafka

●      Work experience with using Databricks (Data Engineering and Delta Lake components) 

●      Experience working with Big Data platforms, including Dataproc, Data Bricks etc

●      Experience working with distributed technology tools including Spark, Presto, Databricks, Airflow

●      Working knowledge of Data warehousing, Data modeling

●      Experience working in Agile and Scrum development process

●      Bachelor's degree in Computer Science, Information Systems, Business, or other relevant subject area

Role:

Senior Data Engineer

Total No. of Years:

8+ years of relevant experience 

To be onboarded by:

Immediate

Notice Period:

Skills

Mandatory / Desirable

Min years (Project Exp)

Max years (Project Exp)

GCP Exposure 

Mandatory Min 3 to 7

BigQuery, Dataflow, Dataproc, AI Building Blocks, Looker, Cloud Data Fusion, Dataprep .Spark and PySpark

Mandatory Min 5 to 9

Relational SQL

Mandatory Min 4 to 8

Shell scripting language 

Mandatory Min 4 to 8

Python /scala language 

Mandatory Min 4 to 8

Airflow/Kubeflow workflow scheduling tool 

Mandatory Min 3 to 7

Kubernetes

Desirable 1 to 6

Scala

Mandatory Min 2 to 6

Databricks

Desirable Min 1 to 6

Google Cloud Functions

Mandatory Min 2 to 6

GitHub source control tool 

Mandatory Min 4 to 8

Machine Learning

Desirable 1 to 6

Deep Learning

Desirable Min 1to 6

Data structures and algorithms

Mandatory Min 4 to 8

Roles and Responsibilities:

• Design, develop, and maintain the end-to-end MLOps infrastructure from the ground up, leveraging open-source systems across the entire MLOps landscape.
• Creating pipelines for data ingestion, data transformation, building, testing, and deploying machine learning models, as well as monitoring and maintaining the performance of these models in production.
• Managing the MLOps stack, including version control systems, continuous integration and deployment tools, containerization, orchestration, and monitoring systems.
• Ensure that the MLOps stack is scalable, reliable, and secure.

Skills Required:

• 3-6 years of MLOps experience
• Preferably worked in the startup ecosystem

Primary Skills:

• Experience with E2E MLOps systems like ClearML, Kubeflow, MLFlow etc.
• Technical expertise in MLOps: Should have a deep understanding of the MLOps landscape and be able to leverage open-source systems to build scalable, reliable, and secure MLOps infrastructure.
• Programming skills: Proficient in at least one programming language, such as Python, and have experience with data science libraries, such as TensorFlow, PyTorch, or Scikit-learn.
• DevOps experience: Should have experience with DevOps tools and practices, such as Git, Docker, Kubernetes, and Jenkins.

Secondary Skills:

• Version Control Systems (VCS) tools like Git and Subversion
• Containerization technologies like Docker and Kubernetes
• Cloud Platforms like AWS, Azure, and Google Cloud Platform
• Data Preparation and Management tools like Apache Spark, Apache Hadoop, and SQL databases like PostgreSQL and MySQL
• Machine Learning Frameworks like TensorFlow, PyTorch, and Scikit-learn
• Monitoring and Logging tools like Prometheus, Grafana, and Elasticsearch
• Continuous Integration and Continuous Deployment (CI/CD) tools like Jenkins, GitLab CI, and CircleCI
• Explain ability and Interpretability tools like LIME and SHAP

THE IDEAL CANDIDATE WILL

• Engage with executive level stakeholders from client's team to translate business problems to high level solution approach
• Partner closely with practice, and technical teams to craft well-structured comprehensive proposals/ RFP responses clearly highlighting Tredence’s competitive strengths relevant to Client's selection criteria
• Actively explore the client’s business and formulate solution ideas that can improve process efficiency and cut cost, or achieve growth/revenue/profitability targets faster
• Work hands-on across various MLOps problems and provide thought leadership
• Grow and manage large teams with diverse skillsets
• Collaborate, coach, and learn with a growing team of experienced Machine Learning Engineers and Data Scientists

ELIGIBILITY CRITERIA

• BE/BTech/MTech (Specialization/courses in ML/DS)
• At-least 7+ years of Consulting services delivery experience
• Very strong problem-solving skills & work ethics
• Possesses strong analytical/logical thinking, storyboarding and executive communication skills
• 5+ years of experience in Python/R, SQL
• 5+ years of experience in NLP algorithms, Regression & Classification Modelling, Time Series Forecasting
• Hands on work experience in DevOps
• Should have good knowledge in different deployment type like PaaS, SaaS, IaaS
• Exposure on cloud technologies like Azure, AWS or GCP
• Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
• Knowledge of Deep Learning frameworks: Keras, Tensorflow, PyTorch, etc
• Experience with one or more Container-ecosystem (Docker, Kubernetes)
• Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint.
• Good understanding of OOP & Data Structures concepts

Nice to Have:

• Exposure to deployment strategies like: Blue/Green, Canary, AB Testing, Multi-arm Bandit
• Experience in Helm is a plus
• Strong understanding of data infrastructure, data warehouse, or data engineering

You can expect to –

• Work with world’ biggest retailers and help them solve some of their most critical problems. Tredence is a preferred analytics vendor for some of the largest Retailers across the globe
• Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices.
• Work in a diverse environment that keeps evolving
• Hone your entrepreneurial skills as you contribute to growth of the organization

Who Are We

A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.

ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.

WHY US

• Join top AI company
• Grow with your best companions
• Continuous pursuit of excellence, equality, respect
• Competitive compensation and benefits

You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.

To learn more about how we work, please check out

https://www.orbo.ai/.

Description:

We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.

Responsibilities:

• Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
• Lead a team of ML engineers in developing an industrial AI product from scratch
• Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
• Tune the models to achieve high accuracy rates and minimum latency
• Deploying developed computer vision models on edge devices after optimization to meet customer requirements

Requirements:

• Bachelor’s degree
• Understanding about depth and breadth of computer vision and deep learning algorithms.
• 4+ years of industrial experience in computer vision and/or deep learning
• Experience in taking an AI product from scratch to commercial deployment.
• Experience in Image enhancement, object detection, image segmentation, image classification algorithms
• Experience in deployment with OpenVINO, ONNXruntime and TensorRT
• Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
• Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
• Proficient understanding of code versioning tools, such as Git

Our perfect candidate is someone that:

• is proactive and an independent problem solver
• is a constant learner. We are a fast growing start-up. We want you to grow with us!
• is a team player and good communicator

What We Offer:

• You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
• You will be in charge of what you build and be an integral part of the product development process
• Technical and financial growth!

Glance – An InMobi Group Company:

Glance is an AI-first Screen Zero content discovery platform, and it’s scaled massively in the last few months to one of the largest platforms in India. Glance is a lock-screen first mobile content platform set up within InMobi. The average mobile phone user unlocks their phone >150 times a day. Glance aims to be there, providing visually rich, easy to consume content to entertain and inform mobile users - one unlock at a time. Glance is live on more than 80 millions of mobile phones in India already, and we are only getting started on this journey! We are now into phase 2 of the Glance story - we are going global!

Roposo is part of the Glance family. It is a short video entertainment platform. All the videos created here are user generated (via upload or Roposo creation tools in camera) and there are many communities creating these videos on various themes we call channels. Around 4 million videos are created every month on Roposo and power Roposo channels, some of the channels are - HaHa TV (for comedy videos), News, Beats (for singing/ dance performances) along with a For You (personalized for a user) and Your Feed (for videos of people a user follows).

What’s the Glance family like?

Consistently featured among the “Great Places to Work” in India since 2017, our culture is our true north, enabling us to think big, solve complex challenges and grow with new opportunities. Glanciers are passionate and driven, creative and fun-loving, take ownership and are results-focused. We invite you to free yourself, dream big and chase your passion.

What can we promise? 

We offer an opportunity to have an immediate impact on the company and our products. The work that you shall do will be mission critical for Glance and will be critical for optimizing tech operations, working with highly capable and ambitious peer groups. At Glance, you get food for your body, soul, and mind with daily meals, gym, and yoga classes, cutting-edge training and tools, cocktails at drink cart Thursdays and fun at work on Funky Fridays. We even promise to let you bring your kids and pets to work. 

What you will be doing?

Glance is looking for a Data Scientist who will design and develop processes and systems to analyze high volume, diverse "big data" sources using advanced mathematical, statistical, querying, and reporting methods. Will use machine learning techniques and statistical analysis to predict outcomes and behaviors. Interacts with business partners to identify questions for data analysis and experiments. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and or prepares output from analysis and experiments to business partners. 

You will be working with Product leadership, taking high-level objectives and developing solutions that fulfil these requirements. Stakeholder management across Eng, Product and Business teams will be required.

Basic Qualifications:

• Five+ years experience working in a Data Science role
• Extensive experience developing and deploying ML models in real world environments
• Bachelor's degree in Computer Science, Mathematics, Statistics, or other analytical fields
• Exceptional familiarity with Python, Java, Spark or other open-source software with data science libraries
• Experience in advanced math and statistics
• Excellent familiarity with command line linux environment
• Able to understand various data structures and common methods in data transformation
• Experience deploying machine learning models and measuring their impact
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

Preferred Qualifications

• Experience developing recommendation systems
• Experience developing and deploying deep learning models
• Bachelor’s or Master's Degree or PhD that included coursework in statistics, machine learning or data analysis
• Five+ years experience working with Hadoop, a NoSQL Database or other big data infrastructure
• Experience with being actively engaged in data science or other research-oriented position
• You would be comfortable collaborating with cross-functional teams.
• Active personal GitHub account.