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2-5 yrs of proven experience in ML, DL, and preferably NLP.
Preferred Educational Background - B.E/B.Tech, M.S./M.Tech, Ph.D.
𝐖𝐡𝐚𝐭 𝐰𝐢𝐥𝐥 𝐲𝐨𝐮 𝐰𝐨𝐫𝐤 𝐨𝐧?
𝟏) Problem formulation and solution designing of ML/NLP applications across complex well-defined as well as open-ended healthcare problems.
2) Cutting-edge machine learning, data mining, and statistical techniques to analyse and utilise large-scale structured and unstructured clinical data.
3) End-to-end development of company proprietary AI engines - data collection, cleaning, data modelling, model training / testing, monitoring, and deployment.
4) Research and innovate novel ML algorithms and their applications suited to the problem at hand.
𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐰𝐞 𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐟𝐨𝐫?
𝟏) Deeper understanding of business objectives and ability to formulate the problem as a Data Science problem.
𝟐) Solid expertise in knowledge graphs, graph neural nets, clustering, classification.
𝟑) Strong understanding of data normalization techniques, SVM, Random forest, data visualization techniques.
𝟒) Expertise in RNN, LSTM, and other neural network architectures.
𝟓) DL frameworks: Tensorflow, Pytorch, Keras
𝟔) High proficiency with standard database skills (e.g., SQL, MongoDB, Graph DB), data preparation, cleaning, and wrangling/munging.
𝟕) Comfortable with web scraping, extracting, manipulating, and analyzing complex, high-volume, high-dimensionality data from varying sources.
𝟖) Experience with deploying ML models on cloud platforms like AWS or Azure.
9) Familiarity with version control with GIT, BitBucket, SVN, or similar.
𝐖𝐡𝐲 𝐜𝐡𝐨𝐨𝐬𝐞 𝐮𝐬?
𝟏) We offer Competitive remuneration.
𝟐) We give opportunities to work on exciting and cutting-edge machine learning problems so you contribute towards transforming the healthcare industry.
𝟑) We offer flexibility to choose your tools, methods, and ways to collaborate.
𝟒) We always value and believe in new ideas and encourage creative thinking.
𝟓) We offer open culture where you will work closely with the founding team and have the chance to influence the product design and execution.
𝟔) And, of course, the thrill of being part of an early-stage startup, launching a product, and seeing it in the hands of the users.
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 is looking for a Data / Sr. Data Scientist who has the knowledge and experience in developing machine learning algorithms, particularly in supply chain and forecasting domain with data science toolkits like Python.
In this role, you will design the approach, develop and test machine learning algorithms, implement the solution. The candidate should have excellent communication skills and be results driven with a customer centric approach to problem solving. Experience working in the demand forecasting or supply chain domain is a plus. This job also requires the ability to operate in a multi-geographic delivery environment and a good understanding of cross-cultural sensitivities.
Responsibilities:
Responsibilities includes, but are not limited to the following:
- Design, build, test, and implement predictive Machine Learning models.
- Collaborate with client to align business requirements with data science systems and process solutions that ensure client’s overall objectives are met.
- Create meaningful presentations and analysis that tell a “story” focused on insights, to communicate the results/ideas to key decision makers.
- Collaborate cross-functionally with domain experts to identify gaps and structural problems.
- Contribute to standard business processes and practices as part of a community of practise.
- Be the subject matter expert across multiple work streams and clients.
- Mentor and coach team members.
- Set a clear vision for the team members and working cohesively to attain it.
Qualifications and Skills:
Requirements
- Experience / Education:
- Master’s or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, Statistics, Applied Mathematics or other related
- 5+ years’ experience working in applied machine learning or relevant research experience for recent Ph.D. graduates.
- Highly technical:
- Skilled in machine learning, problem-solving, pattern recognition and predictive modeling with expertise in PySpark and Python.
- Understanding of data structures and data modeling.
- Effective communication and presentation skills
- Able to collaborate closely and effectively with teams.
- Experience in time series forecasting is preferred.
- Experience working in start-up type environment preferred.
- Experience in CPG and/or Retail preferred.
- Effective communication and presentation skills.
- Strong management track record.
- Strong inter-personal skills and leadership qualities.
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
Antuit.ai is an at-will, equal opportunity employer. We consider applicants for all positions without regard to race, color, religion, national origin or ancestry, gender identity, sex, age (40+), marital status, disability, veteran status, or any other legally protected status under local, state, or federal law.
About us:
Hypersonix.ai is revolutionizing the e-commerce landscape by harnessing the power of AI, ML, and advanced decision capabilities to deliver real-time business insights. Built from the ground up with cutting-edge technology, Hypersonix.ai simplifies data consumption for our diverse range of customers across various industry verticals.
Roles and Responsibilities:
- Collaborate with cross-functional teams in designing, developing, and deploying traditional machine learning models and algorithms for supply chain optimization.
- Conduct research, experimentation, and implementation of state-of-the-art traditional machine learning techniques and frameworks to address complex challenges.
- Develop and enhance forecasting models for demand prediction, inventory management, and pricing optimization.
- Optimize traditional machine learning models for tasks such as inventory forecasting, pricing strategies, and demand forecasting.
- Stay abreast of the latest advancements in traditional machine learning, forecasting techniques, and optimization methods, integrating them into our projects.
- Collaborate closely with data scientists, software engineers, and product teams to seamlessly integrate machine learning solutions into production environments.
- Document research findings, methodologies, and codebase for effective knowledge sharing and team collaboration.
- Troubleshoot and resolve issues in production environments to ensure system reliability and performance.
- Conduct root cause analysis of product defects and implement effective solutions.
- Design, develop, and maintain components of the product to drive customer adoption.
- Utilize various data science methodologies to tackle complex business problems effectively.
Qualifications:
- Strong problem-solving skills and the ability to tackle complex, open-ended challenges.
- Self-motivated individual with a strong work ethic, capable of working independently and collaboratively within a team.
- Proven experience in traditional machine learning, forecasting, pricing, and inventory optimization with a strong portfolio of projects (7-9 years).
- Experience working on NLP and deep learning.
- Proficiency in Python programming and the ability to write efficient, maintainable code.
- Expertise in traditional machine learning libraries and frameworks such as scikit-learn, XGBoost, and LightGBM.
- Experience with cloud-based AI services and infrastructure (e.g., AWS).
- Demonstrated experience in API development and integration.
- Previous experience working in production environments, ensuring system stability and performance.
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
- Bring in industry best practices around creating and maintaining robust data pipelines for complex data projects with/without AI component
- programmatically ingesting data from several static and real-time sources (incl. web scraping)
- rendering results through dynamic interfaces incl. web / mobile / dashboard with the ability to log usage and granular user feedbacks
- performance tuning and optimal implementation of complex Python scripts (using SPARK), SQL (using stored procedures, HIVE), and NoSQL queries in a production environment
- Industrialize ML / DL solutions and deploy and manage production services; proactively handle data issues arising on live apps
- Perform ETL on large and complex datasets for AI applications - work closely with data scientists on performance optimization of large-scale ML/DL model training
- Build data tools to facilitate fast data cleaning and statistical analysis
- Ensure data architecture is secure and compliant
- Resolve issues escalated from Business and Functional areas on data quality, accuracy, and availability
- Work closely with APAC CDO and coordinate with a fully decentralized team across different locations in APAC and global HQ (Paris).
You should be
- Expert in structured and unstructured data in traditional and Big data environments – Oracle / SQLserver, MongoDB, Hive / Pig, BigQuery, and Spark
- Have excellent knowledge of Python programming both in traditional and distributed models (PySpark)
- Expert in shell scripting and writing schedulers
- Hands-on experience with Cloud - deploying complex data solutions in hybrid cloud / on-premise environment both for data extraction/storage and computation
- Hands-on experience in deploying production apps using large volumes of data with state-of-the-art technologies like Dockers, Kubernetes, and Kafka
- Strong knowledge of data security best practices
- 5+ years experience in a data engineering role
- Science / Engineering graduate from a Tier-1 university in the country
- And most importantly, you must be a passionate coder who really cares about building apps that can help people do things better, smarter, and faster even when they sleep
Duties and Responsibilities:
Research and Develop Innovative Use Cases, Solutions and Quantitative Models
Quantitative Models in Video and Image Recognition and Signal Processing for cloudbloom’s
cross-industry business (e.g., Retail, Energy, Industry, Mobility, Smart Life and
Entertainment).
Design, Implement and Demonstrate Proof-of-Concept and Working Proto-types
Provide R&D support to productize research prototypes.
Explore emerging tools, techniques, and technologies, and work with academia for cutting-
edge solutions.
Collaborate with cross-functional teams and eco-system partners for mutual business benefit.
Team Management Skills
Academic Qualification
7+ years of professional hands-on work experience in data science, statistical modelling, data
engineering, and predictive analytics assignments
Mandatory Requirements: Bachelor’s degree with STEM background (Science, Technology,
Engineering and Management) with strong quantitative flavour
Innovative and creative in data analysis, problem solving and presentation of solutions.
Ability to establish effective cross-functional partnerships and relationships at all levels in a
highly collaborative environment
Strong experience in handling multi-national client engagements
Good verbal, writing & presentation skills
Core Expertise
Excellent understanding of basics in mathematics and statistics (such as differential
equations, linear algebra, matrix, combinatorics, probability, Bayesian statistics, eigen
vectors, Markov models, Fourier analysis).
Building data analytics models using Python, ML libraries, Jupyter/Anaconda and Knowledge
database query languages like SQL
Good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM,
Decision Forests.
Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the
fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis
of a lot of predictive performance or algorithm optimization techniques.
Deep learning : CNN, neural Network, RNN, tensorflow, pytorch, computervision,
Large-scale data extraction/mining, data cleansing, diagnostics, preparation for Modeling
Good applied statistical skills, including knowledge of statistical tests, distributions,
regression, maximum likelihood estimators, Multivariate techniques & predictive modeling
cluster analysis, discriminant analysis, CHAID, logistic & multiple regression analysis
Experience with Data Visualization Tools like Tableau, Power BI, Qlik Sense that help to
visually encode data
Excellent Communication Skills – it is incredibly important to describe findings to a technical
and non-technical audience
Capability for continuous learning and knowledge acquisition.
Mentor colleagues for growth and success
Strong Software Engineering Background
Hands-on experience with data science tools