10+ Time series Jobs in India

About Moative

Moative, an Applied AI Services company, designs AI roadmaps, builds co-pilots and predictive AI solutions for companies in energy, utilities, packaging, commerce, and other primary industries. Through Moative Labs, we aspire to build micro-products and launch AI startups in vertical markets. 

We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.

Work you’ll do

As a data scientist, you will lead data-driven projects, design and develop advanced analytical frameworks and AI/ML solutions to address business problems. You will collaborate with product managers, engineers and domain experts to deliver intelligent solutions and products.

You’ll analyze new opportunities and ideas, evaluate new AI/ ML models/ frameworks/ platforms, conduct experiments, develop PoCs and prototypes.

As a Data Scientist, you will provide your advanced expertise on statistical and mathematical concepts and guide the team in AI/ML algorithms and model development. You will stay up-to-date with the latest advancements in data science, machine learning, and AI.

The ideal candidate will have a strong background in statistics, machine learning, and programming, as well as excellent business understanding and product design thinking skills. If you are passionate about data and have a proven track record of delivering impactful data solutions, we would love to hear from you.

Responsibilities

• Frame problems before you model them. You will define the problem structure, identify the right success metric, and map failure modes — data drift, integration cost, adoption friction — before a single model is trained. Post-mortems are not your primary output; pre-mortems are.
• Own delivery end-to-end, including deployment. You will take models from scoping through production. If your best work is a notebook that never shipped, this role is not for you. You will own the last mile: deployment, monitoring, iteration in production.
• Sit embedded in client teams and hold the room. You will join client standups, present modelling choices to client leadership, and defend or revise your approach on the spot. You will be the technical voice accountable for outcomes — not a back-office supplier of models.
• Build accelerators and reusable frameworks, not one-offs. You will identify repeatable patterns across engagements and convert them into tools, templates, and internal infrastructure that make the next delivery faster and more defensible.
• Write and communicate with precision across audiences. You will produce decision memos, model cards, and post-mortems that are specific enough for an engineer and clear enough for a CFO. You will cover trade-offs, assumptions, and risks — in the same meeting, for both rooms, without dumbing either one down.
• Drive ML lifecycle discipline. You will establish and enforce best practices across model development, versioning, evaluation, and monitoring — and raise the bar for how the team thinks about model quality and production readiness.

Who you are

You are a data scientist who is passionate about using AI/ML to improve processes, products and delight customers. You have experience working with less than clean data, developing ML models, and orchestrating the deployment of them to production. You thrive on taking initiatives, are very comfortable with ambiguity and can passionately defend your decisions.

Requirements and skills

• 2+ years of hands-on data science with shipped production models. Evidence of models that moved from development to deployment with measurable business impact. "Worked on" does not qualify — you must have owned the outcome.
• Consumer-scale domain depth in a regulated or operationally sensitive business. Direct experience with one or more of: credit risk and portfolio modelling (PD/LGD/EAD, scorecards, alternative-data underwriting, collections or behavioural scoring) or retail and commerce modelling (demand forecasting with seasonality and promo effects, assortment and markdown optimisation, customer segmentation and LTV, returns prediction, pricing elasticity). You can read a delinquency curve, or a sell-through curve, or a cohort retention plot and know what it implies for the next model decision and the next business decision
• Production GenAI and agentic system experience beyond prompt engineering. Hands-on with retrieval design, eval harnesses, guardrails, and fine-tuning vs. prompting trade-offs. You understand the observability and cost discipline required to run these systems in production. Prompt engineering alone does not qualify.
• Cloud and MLOps fluency. Proficient across at least one major cloud (AWS, Azure, or GCP) and experienced with MLOps tooling — MLflow, model registries, CI/CD for ML, and drift monitoring in production.
• Client-facing delivery experience. Has worked directly with external clients or business stakeholders — not just internal teams. Comfortable presenting technical choices, fielding pushback, and adjusting in real time without losing the thread.
• Structural problem framing, not just modelling skill. Demonstrates the ability to define what problem is actually worth solving, choose the right analytical approach for the business context, and articulate why alternative approaches were rejected.

Working at Moative

Moative is a young company, but we believe strongly in thinking long-term, while acting with urgency. Our ethos is rooted in innovation, efficiency and high-quality outcomes. We believe the future of work is AI-augmented and boundary less.

Here are some of our guiding principles:

• Think in decades. Act in hours. As an independent company, our moat is time. While our decisions are for the long-term horizon, our execution will be fast – measured in hours and days, not weeks and months.
• Own the canvas. Throw yourself in to build, fix or improve – anything that isn’t done right, irrespective of who did it. Be selfish about improving across the organization – because once the rot sets in, we waste years in surgery and recovery.
• Use data or don’t use data. Use data where you ought to but not as a ‘cover-my-back’ political tool. Be capable of making decisions with partial or limited data. Get better at intuition and pattern-matching. Whichever way you go, be mostly right about it.
• Avoid work about work. Process creeps on purpose, unless we constantly question it. We are deliberate about committing to rituals that take time away from the actual work. We truly believe that a meeting that could be an email, should be an email and you don’t need a person with the highest title to say that out loud.
• High revenue per person. We work backwards from this metric. Our default is to automate instead of hiring. We multi-skill our people to own more outcomes than hiring someone who has less to do. We don’t like squatting and hoarding that comes in the form of hiring for growth. High revenue per person comes from high quality work from everyone. We demand it.

If this role and our work is of interest to you, please apply here. We encourage you to apply even if you believe you do not meet all the requirements listed above.

The position is based out of Chennai. Our work currently involves significant in-person collaboration and we expect you to be present in the city

Company name: JPMorgan (JPMC)

Job Category:
 Predictive Science

Location: Parcel 9, Embassy Tech Village, Outer Ring Road, Deverabeesanhalli Village, Varthur Hobli, Bengaluru

Job Schedule: 
Full time

JOB DESCRIPTION

JPMC is hiring the best talents to join the growing Asset and Wealth Management AI team. We are executing like a startup and building next-generation technology that combines JPMC unique data and full-service advantage to develop high impact AI applications and platforms in the financial services industry. We are looking for hands-on ML Engineering leader and expert who is excited about the opportunity. 

As a senior ML and GenAI engineer, you will play a lead role as a senior member of our global team. Your responsibilities will entail hands on development of high-impact business solutions through data analysis, developing cutting edge ML and LLM models, and deploying these models to production environments on AWS or Azure. 

You'll combine your years of proven development expertise with a never-ending quest to create innovative technology through solid engineering practices. Your passion and experience in one or more technology domains will help solve complex business problems to serve our Private Bank clients. As a constant learner and early adopter, you’re already embracing leading-edge technologies and methodologies; your example encourages others to follow suit. 

 Job responsibilities 

• Hands-on architecture and implementation of lighthouse ML and LLM-powered solutions 

• Close partnership with peers in a geographically dispersed team and colleagues across organizational lines 

• Collaborate across JPMorgan AWM’s lines of business and functions to accelerate adoption of common AI capabilities 

• Design and implement highly scalable and reliable data processing pipelines and deploy model inference services. 

• Deploy solutions into public cloud infrastructure 

• Experiment, develop and productionize high quality machine learning models, services, and platforms to make a huge technology and business impact 

 Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience

• MS in Computer Science, Statistics, Mathematics or Machine Learning. 

• Development experience, along with hands-on Machine Learning Engineering 

• Proven leadership capacity, including new AI/ML idea generation and GenAI-based solutions 

• Solid Python programming skills required; with other high-performance language such as Go a big plus 

• Expert knowledge of one of the cloud computing platforms preferred: Amazon Web Services (AWS), Azure, Kubernetes. 

• Experience in using LLMs (OpenAI, Claude or other models) to solve business problems, including full workflow toolset, such as tracing, evaluations and guardrails. Understanding of LLM fine-tuning and inference a plus 

• Knowledge of data pipelines, both batch and real-time data processing on both SQL (such as Postgres) and NoSQL stores (such as OpenSearch and Redis) 

• Expertise in application, data, and infrastructure architecture disciplines 

• Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics. 

• Excellent communication skills and ability to communicate with senior technical and business partners 

 Preferred qualifications, capabilities, and skills

• Expert in at least one of the following areas: Natural Language Processing, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis. 

• Knowledge of machine learning frameworks: Pytorch, Keras, MXNet, Scikit-Learn 

• Understanding of finance or wealth management businesses is an added advantage 

ABOUT US

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

ABOUT THE TEAM

J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.

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.

• 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