10+ Time series Jobs in India

About the Role

We are looking for a highly motivated Demand Forecasting Analyst with hands-on experience in building, improving, and managing demand forecasting models for retail businesses. The candidate will play a key role in leveraging data-driven forecasting techniques to optimize inventory, improve supply chain efficiency, and enhance business decision-making. 

The role requires strong business understanding of retail operations, combined with technical expertise in AWS cloud services, forecasting techniques, and stakeholder communications.

Key Responsibilities

• Develop, implement, and maintain demand forecasting models tailored to retail business needs.
• Analyze historical sales data, seasonal patterns, promotions, and external market factors to improve forecast accuracy.
• Collaborate with cross-functional teams (merchandising, supply chain, finance) to understand business requirements and translate them into forecasting solutions.
• Leverage AWS services (Amazon Forecast, S3, Lambda, Glue, Redshift, QuickSight, SageMaker, etc.) for data preparation, modelling, deployment, and reporting.
• Continuously monitor forecast performance and refine models to reduce forecast error (MAPE, WAPE, etc.).
• Provide actionable insights and recommendations to stakeholders for inventory management, pricing, and demand planning.
• Create dashboards and reports to track key forecasting KPIs for business teams.

Required Qualifications

• 1–2 years of experience in demand forecasting within retail (FMCG, e-commerce, fashion, or grocery retail preferred).
• Strong understanding of retail demand drivers such as seasonality, promotions, new product launches, and external factors.
• Hands-on experience with AWS services such as:
• Amazon Forecast for building forecasting models.
• Amazon S3, Glue, Redshift for data storage and ETL.
• Amazon SageMaker for model customization and fine-tuning.
• Amazon QuickSight for reporting and dashboards.
• Proficiency in Python for data analysis and modelling.
• Familiarity with forecasting methods (ARIMA, DeepAR, Prophet, ML-based forecasting, regression, etc.).
• Strong analytical skills with the ability to interpret data and provide business insights.
• Excellent communication and presentation skills to interact with both technical and non-technical stakeholders.

Good to Have

• Experience with time-series modelling in retail.
• Knowledge of inventory optimization and supply chain planning.

Why Join Us?

• Opportunity to work on cutting-edge demand forecasting projects in the retail domain.
• Leverage AWS cloud-native solutions for scalable, real-world impact.
• Collaborate with business and technology leaders to shape retail strategy.
• Fast-paced, growth-oriented environment with career development opportunities.

We're hiring an experienced SAP IBP Consultant with 6+ years of expertise in Demand and Supply Planning. The ideal candidate should have strong skills in key figure modeling, time series planning, and integration with S/4HANA or ECC. Prior experience with planning operators, forecast models, and Excel Add-in is required.

Lifespark is looking for individuals with a passion for impacting real lives through technology. Lifespark is one of the most promising startups in the Assistive Tech space in India, and has been honoured with several National and International awards. Our mission is to create seamless, persistent and affordable healthcare solutions. If you are someone who is driven to make a real impact in this world, we are your people.

Lifespark is currently building solutions for Parkinson’s Disease, and we are looking for a ML lead to join our growing team. You will be working directly with the founders on high impact problems in the Neurology domain. You will be solving some of the most fundamental and exciting challenges in the industry and will have the ability to see your insights turned into real products every day

Essential experience and requirements:

1. Advanced knowledge in the domains of computer vision, deep learning

2. Solid understand of Statistical / Computational concepts like Hypothesis Testing, Statistical Inference, Design of Experiments and production level ML system design

3. Experienced with proper project workflow

4. Good at collating multiple datasets (potentially from different sources)

5. Good understanding of setting up production level data pipelines

6. Ability to independently develop and deploy ML systems to various platforms (local and cloud)

7. Fundamentally strong with time-series data analysis, cleaning, featurization and visualisation

8. Fundamental understanding of model and system explainability

9. Proactive at constantly unlearning and relearning

10. Documentation ninja - can understand others documentation as well as create good documentation

Responsibilities :

1. Develop and deploy ML based systems built upon healthcare data in the Neurological domain

2. Maintain deployed systems and upgrade them through online learning

3. Develop and deploy advanced online data pipelines

Dolat Capital is a multi-strategy trading firm, dedicated to producing superior returns by adhering to mathematical and statistical techniques. We trade actively in all Asset classes: equities, futures, options, commodities, currencies and fixed income taking advantage of our ultra-low latency infrastructure. Our low latency infrastructure is in C++, one of the most competitive in terms of latency.

The Quantitative Research team at Dolat Capital focuses on quantitative trading, specifically fully automated trading systems. We develop proprietary algorithms by using mathematical techniques and statistical analysis to identify patterns and behavior of markets.

The incumbent will be responsible to design, develop and implement computational algorithms/strategies that succeed in generating sizable profits consistently, in real life market for a high-frequency trading environment

Job Description: Data Scientist

At Propellor.ai, we derive insights that allow our clients to make scientific decisions. We believe in demanding more from the fields of Mathematics, Computer Science, and Business Logic. Combine these and we show our clients a 360-degree view of their business. In this role, the Data Scientist will be expected to work on Procurement problems along with a team-based across the globe.

We are a Remote-First Company.

Read more about us here: https://www.propellor.ai/consulting" target="_blank">https://www.propellor.ai/consulting

What will help you be successful in this role

• Articulate
• High Energy
• Passion to learn
• High sense of ownership
• Ability to work in a fast-paced and deadline-driven environment
• Loves technology
• Highly skilled at Data Interpretation
• Problem solver
• Ability to narrate the story to the business stakeholders
• Generate insights and the ability to turn them into actions and decisions

Skills to work in a challenging, complex project environment

• Need you to be naturally curious and have a passion for understanding consumer behavior
• A high level of motivation, passion, and high sense of ownership
• Excellent communication skills needed to manage an incredibly diverse slate of work, clients, and team personalities
• Flexibility to work on multiple projects and deadline-driven fast-paced environment
• Ability to work in ambiguity and manage the chaos

Key Responsibilities

• Analyze data to unlock insights: Ability to identify relevant insights and actions from data.  Use regression, cluster analysis, time series, etc. to explore relationships and trends in response to stakeholder questions and business challenges.   
• Bring in experience for AI and ML:  Bring in Industry experience and apply the same to build efficient and optimal Machine Learning solutions.
• Exploratory Data Analysis (EDA) and Generate Insights: Analyse internal and external datasets using analytical techniques, tools, and visualization methods. Ensure pre-processing/cleansing of data and evaluate data points across the enterprise landscape and/or external data points that can be leveraged in machine learning models to generate insights. 
• DS and ML Model Identification and Training: Identity, test, and train machine learning models that need to be leveraged for business use cases. Evaluate models based on interpretability, performance, and accuracy as required. Experiment and identify features from datasets that will help influence model outputs.  Determine what models will need to be deployed, data points that need to be fed into models, and aid in the deployment and maintenance of models.

Technical Skills

An enthusiastic individual with the following skills. Please do not hesitate to apply if you do not match all of them. We are open to promising candidates who are passionate about their work, fast learners and are team players.

• Strong experience with machine learning and AI including regression, forecasting, time series, cluster analysis, classification, Image recognition, NLP, Text Analytics and Computer Vision.
• Strong experience with advanced analytics tools for Object-oriented/object function scripting using languages such as Python, or similar.
• Strong experience with popular database programming languages including SQL.
• Strong experience in Spark/Pyspark
• Experience in working in Databricks

What are the company benefits you get, when you join us as?

• Permanent Work from Home Opportunity
• Opportunity to work with Business Decision Makers and an internationally based team
• The work environment that offers limitless learning
• A culture void of any bureaucracy, hierarchy
• A culture of being open, direct, and with mutual respect
• A fun, high-caliber team that trusts you and provides the support and mentorship to help you grow
• The opportunity to work on high-impact business problems that are already defining the future of Marketing and improving real lives

To know more about how we work: https://bit.ly/3Oy6WlE" target="_blank">https://bit.ly/3Oy6WlE

Whom will you work with?

You will closely work with other Senior Data Scientists and Data Engineers.

Immediate to 15-day Joiners will be preferred.

Job Description

We are looking for an experienced engineer to join our data science team, who will help us design, develop, and deploy machine learning models in production. You will develop robust models, prepare their deployment into production in a controlled manner, while providing appropriate means to monitor their performance and stability after deployment.

What You’ll Do will include (But not limited to):

• Preparing datasets needed to train and validate our machine learning models
• Anticipate and build solutions for problems that interrupt availability, performance, and stability in our systems, services, and products at scale.
• Defining and implementing metrics to evaluate the performance of the models, both for computing performance (such as CPU & memory usage) and for ML performance (such as precision, recall, and F1)
• Supporting the deployment of machine learning models on our infrastructure, including containerization, instrumentation, and versioning
• Supporting the whole lifecycle of our machine learning models, including gathering data for retraining, A/B testing, and redeployments
• Developing, testing, and evaluating tools for machine learning models deployment, monitoring, retraining.
• Working closely within a distributed team to analyze and apply innovative solutions over billions of documents
• Supporting solutions ranging from rule-bases, classical ML techniques  to the latest deep learning systems.
• Partnering with cross-functional team members to bring large scale data engineering solutions to production
• Communicating your approach and results to a wider audience through presentations

Your Qualifications:

• Demonstrated success with machine learning in a SaaS or Cloud environment, with hands–on knowledge of model creation and deployments in production at scale
• Good knowledge of traditional machine learning methods and neural networks
• Experience with practical machine learning modeling, especially on time-series forecasting, analysis, and causal inference.
• Experience with data mining algorithms and statistical modeling techniques for anomaly detection in time series such as clustering, classification, ARIMA, and decision trees is preferred.
• Ability to implement data import, cleansing and transformation functions at scale
• Fluency in Docker, Kubernetes
• Working knowledge of relational and dimensional data models with appropriate visualization techniques such as PCA.
• Solid English skills to effectively communicate with other team members

Due to the nature of the role, it would be nice if you have also:

• Experience with large datasets and distributed computing, especially with the Google Cloud Platform
• Fluency in at least one deep learning framework: PyTorch, TensorFlow / Keras
• Experience with No–SQL and Graph databases
• Experience working in a Colab, Jupyter, or Python notebook environment
• Some experience with monitoring, analysis, and alerting tools like New Relic, Prometheus, and the ELK stack
• Knowledge of Java, Scala or Go-Lang programming languages
• Familiarity with KubeFlow
• Experience with transformers, for example the Hugging Face libraries
• Experience with OpenCV

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

#LI-Remote

• 3+ years experience in practical implementation and deployment of ML based systems preferred.
• BE/B Tech or M Tech (preferred) in CS/Engineering with strong mathematical/statistical background
• Strong mathematical and analytical skills, especially statistical and ML techniques, with familiarity with different supervised and unsupervised learning algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimisation
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python
• Experience in developing and deploying on cloud (AWS or Google or Azure)
• Good verbal and written communication skills
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow

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

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