149 Arima Jobs - Page 4

Job Title: Advanced Machine Learning Tutor Location: Fully Remote Type: Part-Time (Weekend Only) Salary: ₹40,000 – ₹50,000 per month Role Overview We are seeking a skilled and passionate Advanced Machine Learning Tutor to teach learners who have already completed foundational ML topics. You will conduct remote weekend classes , mentor students through hands-on projects, and explain the real-world use of advanced algorithms and techniques. This role is perfect for ML professionals who love teaching, enjoy simplifying complex ideas, and want to make a real impact on career-oriented learners. Key Responsibilities Deliver live weekend sessions on advanced ML concepts, such as: Ensemble Methods (Bagging, Boosting, Stacking) Feature Engineering and Selection Techniques Model Evaluation & Validation (Cross-Validation, ROC-AUC, etc.) Unsupervised Learning (PCA, Clustering techniques like K-Means, DBSCAN) Time Series Forecasting (ARIMA, Prophet, LSTM basics) Hyperparameter Tuning (GridSearchCV, RandomizedSearch, Bayesian Optimization) Introduction to Deep Learning (optional, depending on scope) Guide students through project-based learning using real-world datasets. Support students with doubts, debugging, and tool usage (like scikit-learn, XGBoost, LightGBM). Collaborate on curriculum refinement and improve content delivery. Keep updated with current trends in ML and bring them into your teaching. Required Qualifications Strong experience in Machine Learning beyond basic models Proficient with Python, NumPy, pandas, scikit-learn, XGBoost, etc. Familiar with advanced concepts like model selection, bias-variance tradeoff, overfitting/underfitting solutions Ability to explain and mentor real-world ML projects Previous teaching, tutoring, or mentoring experience (preferred) Excellent communication and presentation skills Nice to Have Familiarity with MLOps basics and tools (like MLflow) Experience with real-time or production ML systems Exposure to research papers or Kaggle competitions Understanding of Time Series and basic DL models like LSTMs Prior educational or ed-tech experience Students Will Learn To: Build and fine-tune complex ML models Evaluate model performance using advanced techniques Work with imbalanced datasets and noise Engineer features for better accuracy Solve real-world problems (credit risk, fraud detection, forecasting, etc.)

Job Description: We are seeking a skilled AI Engineer with 2-4 years of experience to design, develop, and deploy AI/ML solutions, with a strong emphasis on Generative AI, NLP, Retrieval-Augmented Generation (RAG), and Time Series Forecasting. The ideal candidate will have hands-on experience with LangGraph and other Generative AI frameworks to build cutting-edge AI applications. Key Responsibilities Develop and deploy AI/ML models with a focus on NLP, Generative AI, RAG, and Time Series Forecasting workflows. Engineer and refine prompts to optimize performance for large language models (LLMs) and generative AI applications. Implement and maintain data preprocessing pipelines, including data cleansing, feature engineering, embedding generation, and transformation for time series data. Develop end-to-end solutions integrating LLMs with VectorDB (e.g., Weaviate, Pinecone, FAISS) for document retrieval, semantic search, and contextual query answering. Utilize LangGraph and other Generative AI frameworks to build structured workflows for LLM-based applications. Train and fine-tune machine learning models, including LLMs, to optimize performance for various use cases. Analyze and interpret complex datasets, including time series data, ensuring scalable and efficient AI model deployment. Collaborate with cross-functional teams to integrate AI/ML models into existing systems and workflows. Ensure models are robust, scalable, and adhere to best practices in ethical AI development. Conduct testing, performance benchmarking, and iterative refinements of AI models and pipelines. Stay updated with the latest advancements in AI/ML, NLP, and cloud technologies and recommend integration strategies for emerging tools and techniques. Create technical documentation and presentations to effectively communicate AI concepts to stakeholders. Required Skills Key Skills and Qualifications: AI/ML Expertise: Proven experience in developing, fine-tuning, and deploying AI/ML models, focusing on NLP, Generative AI, and Time Series Forecasting. Prompt Engineering: Proficiency in designing, testing, and optimizing prompts for LLMs. Data Analysis: Strong ability to process and interpret large and complex datasets, including time series data, for AI model training and validation. Programming: Proficiency in Python and experience with AI/ML frameworks like TensorFlow, PyTorch, and scikit-learn. NLP Techniques: Understanding of tokenization, embeddings, transformer-based models (e.g., BERT, GPT, LLaMA), and RAG workflows. Vector Databases: Experience with Weaviate, Pinecone, FAISS, or similar VectorDBs for document retrieval and storage. LangGraph & GenAI Frameworks: Hands-on experience with LangGraph, LangChain, HuggingFace Transformers, OpenAI API, and other Generative AI tools. Cloud Deployment: Familiarity with deploying AI solutions on AWS, GCP, or Azure. Time Series Forecasting: Experience with ARIMA, LSTM, Prophet, and other forecasting techniques. Model Training & Fine-Tuning: Ability to train and fine-tune machine learning models, including large language models (LLMs), to enhance performance and accuracy. Problem-Solving & Collaboration: Strong analytical, problem-solving, and teamwork skills to work effectively in a cross-functional environment. Preferred Skills Experience in implementing RAG workflows and integrating generative AI with retrieval-based systems. Familiarity with ethical AI principles and compliance frameworks. Knowledge of additional programming languages such as JavaScript or SQL. Proficiency in MLOps practices for automating AI/ML pipelines and lifecycle management. Experience in developing AI-driven applications for real-world industry use cases. Skills: retrieval-augmented generation (rag),neuro-linguistic programming (nlp),data analysis,collaboration,programming,forecasting,prompt engineering,pytorch,cloud deployment,generative ai frameworks,programming in python,time series forecasting,langgraph & genai frameworks,vector databases (weaviate, pinecone, faiss),problem-solving & collaboration,langgraph & genai frameworks (langchain, huggingface transformers, openai api),ai ml,gen ai,vector databases,time series forecasting (arima, lstm, prophet),model training & fine-tuning,scikit-learn,problem-solving,tensorflow,langgraph,cloud deployment (aws, gcp, azure),nlp techniques,programming (python),mlops,ai/ml expertise

We are looking for a Data Scientist to help us gain useful insight from raw data. Data scientists' responsibilities include working with the data science team, planning projects, and building analytics models. You should have a strong problem-solving ability and a knack for statistical analysis. If you're also able to align our data products with our business goals, we'd like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data. Responsibilities Responsible for overseeing the data scientists' team and data specialists. Teach, lead, and counsel colleagues on new techniques or solutions. Collaborate with data and software engineers to enable the deployment of sciences and technologies that will scale across the company's ecosystem. Responsible for the conception, planning, and prioritizing of data projects. Responsible for building analytic systems and predictive models, as well as experimenting with new models and techniques. Ensure that data projects align with organizational goals. Requirements Master's degree in Computer Science, Operations Research, Econometrics, Statistics, or related technical field. 3+ years of experience solving analytical problems using quantitative approaches. Experience communicating quantitative analysis results. Knowledge of relational databases and SQL. Development experience in any scripting language (PHP, Python, Perl, etc. ). Knowledge of statistics (e. g., hypothesis testing, regression). Experience manipulating data sets through statistical software (ex., R, SAS) or other methods. Must Have Programming - Python (Preferred) / R. ML Models - i. Regression - Linear, Logistic, Multinomial, Mixed effect. Classification - Bagging and Boosting (Random Forest), Decision tree, SVM. Clustering - K-Means, hierarchical, DB-Scan. Time series - ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS (VAR), UCM, Neural Networks (Deep learning), Naive Bayes, Excel, and SQL. Dimensionality Reduction - PCA, SVD, etc. Optimization Techniques - Linear programming, Gradient Descent, Genetic Algorithm. Cloud - Understanding of Azure / AWS offerings, setting up an ML pipeline in the cloud. Good To Have Visualization - Tableau / Power BI / Looker / QlikView. Data management - HDFS, Spark, Advanced Excel. Agile Tools - Azure DevOps, JIRA, Pyspark, Big Data/Hive Database. IDE: PyCharm. This job was posted by Debapti Roy from mPokket.

Dear Candidate, Greetings from Global Healthcare Billing Partners Pvt Ltd! We are pleased to inform you about Opening with the Global Healthcare for the profile of CHARGE ENTRY & PAYMENT POSTING!!! Experience : 1Years - 6 Years Qualification : Any Graduate Notice: Immediate Joiner. Essential Requirement :- Associate should have worked Experience in Charge entry & Payment Posting with good knowledge of medical billing process. Location: Velachery & Vepery Shift: Day Contact Name : MALINI HR Contact Details - 9003239650 / 8925808598 (Call or Whatsapp) NOTE : (only Medical billing experience with 1Yrs are eligible) Regards MALINI HR GLOBAL

Primary Skills Time Series Forecasting : Applying models like ARIMA, Prophet, or LSTM for month-on-month estimations Machine Learning : Building and deploying ML models for forecasting and cost optimization Python Programming : For data manipulation, modeling, and automation (Pandas, NumPy, scikit-learn) CDN Domain Knowledge : Understanding content delivery networks, traffic patterns, and cost structures Power BI : Designing dashboards for CDN usage reporting (regional, brand-level, etc.) Data Analysis & Modeling : Statistical analysis, feature engineering, and model evaluation Cost Optimization Techniques : Using ML to model and optimize CDN allocation and expenses SQL : Querying structured data for reporting and model input Secondary Skills These enhance effectiveness and collaboration but are not strictly mandatory: Cloud Platforms : Familiarity with Azure, AWS, or GCP for data storage and compute ETL & Data Wrangling : Preparing and transforming data from multiple sources Version Control : Using Git for code collaboration and tracking Agile Methodologies : Working in sprints, using tools like JIRA or Confluence Communication Skills : Explaining technical insights to non-technical stakeholders Collaboration Tools : Experience with Teams, Slack, or similar platforms This job is provided by Shine.com

Mandatory leadership experience is required & responsible for managing a team of 50+ associates under at least 2-3 team leads. Responsible for timely and accurate posting of all payments. Experience in Payment posting, Denials Postings and Insurance rejections & Claims. Responsible to handle team and maintain teams production & quality, client coordination Should Possess extensive knowledge in Reviewing Explanation of Benefits (EOB) and Electronic remittance advice (ERA) documents, matches with electronic funds transfers (EFTs) and post payment to appropriate accounts. This Role involves extensive knowledge in Payment and Denial Posting, ERA posting, Correspondence posting, Insurance Portals, Bank Reconciliations, Marchant portals, Refund process, Statement and Collection process, EOM Reporting. Excellent skill sets required in Microsoft products, especially excel spreadsheet for reports and analyze data using tools like VLOOKUP. Pivot table etc. The right candidate should be able to handle the work pressure during End of Month and will take the challenge to meet the day-to-day deliverables. Ensuring the Daily/Weekly and Monthly reports are to be shared with the stakeholders in a timely manner and within the given time. Good communication and interpersonal skills especially with the team members and clients. Preferred Only Immediate Joiner Salary will not be a constraint to a right candidate & at par with the Industry standard.

Job Responsibilities: Claim Verification: Verify and review healthcare claims to ensure accuracy and completeness. Learn to identify common billing errors and discrepancies in claim submissions. Initiate Follow-up Calls: Make outbound calls to insurance companies to inquire about the status of claims. Gain exposure to professional communication and develop rapport with insurance representatives. Research Denials and Underpayments: Investigate reasons for claim denials and underpayments. Work closely with senior AR Callers to understand denial codes and resolution strategies. Assist in Appeal Preparation: Support in the preparation of appeal packets for denied or underpaid claims. Learn the documentation and submission process for appeals. Claim Corrections: Understand the basics of correcting errors on claims and resubmitting them. Collaborate with team members to rectify common billing mistakes. Documentation and Reporting: Maintain accurate records of communication and actions taken in the claims billing system. Assist in generating basic reports related to claim status and follow-up activities. Training and Skill Development: Actively participate in training programs provided by the company. Continuously enhance knowledge of medical billing and coding practices.

Location: Gurugram, India Position Summary We are seeking a highly motivated and analytical Quant Analyst to join Futures First. The role involves supporting development and execution of quantitative strategies across financial markets. Job Profile Statistical Arbitrage & Strategy Development Design and implement pairs, mean-reversion, and relative value strategies in fixed income (govvies, corporate bonds, IRS). Apply cointegration tests (Engle-Granger, Johansen), Kalman filters, and machine learning techniques for signal generation. Optimize execution using transaction cost analysis (TCA). Correlation & Volatility Analysis Model dynamic correlations between bonds, rates, and macro variables using PCA, copulas, and rolling regressions. Forecast yield curve volatility using GARCH, stochastic volatility models, and implied-vol surfaces for swaptions. Identify regime shifts (e.g., monetary policy impacts) and adjust strategies accordingly. Seasonality & Pattern Recognition Analyse calendar effects (quarter-end rebalancing, liquidity patterns) in sovereign bond futures and repo markets. Develop time-series models (SARIMA, Fourier transforms) to detect cyclical trends. Back Testing & Automation Build Python-based back testing frameworks (Backtrader, Qlib) to validate strategies. Automate Excel-based reporting (VBA, xlwings) for P&L attribution and risk dashboards. Integrate Bloomberg/Refinitiv APIs for real-time data feeds. Requirements Education Qualifications B.Tech Work Experience 0-3 years Skill Set Must have: Strong grasp of probability theory, stochastic calculus (Itos Lemma, SDEs), and time-series econometrics (ARIMA, VAR, GARCH). Must have: Expertise in linear algebra (PCA, eigenvalue decomposition), numerical methods (Monte Carlo, PDE solvers), and optimization techniques. Preferred: Knowledge of Bayesian statistics, Markov Chain Monte Carlo (MCMC), and machine learning (supervised/unsupervised learning). Libraries: NumPy, Pandas, statsmodels, scikit-learn, arch (GARCH models). Back testing: Backtrader, Zipline, or custom event-driven frameworks. Data handling: SQL, Dask (for large datasets). Power Query, pivot tables, Bloomberg Excel functions (BDP, BDH). VBA scripting for various tools and automation. Experience with C /Java (low-latency systems), QuantLib (fixed income pricing), or R (statistical). Yield curve modelling (Nelson-Siegel, Svensson), duration/convexity, OIS pricing. Credit spreads, CDS pricing, and bond-CDS basis arbitrage. Familiarity with VaR, CVaR, stress testing, and liquidity risk metrics. Understanding of CCIL, NDS-OM (Indian market infrastructure). Ability to translate intuition and patterns into quant models. Strong problem-solving and communication skills (must explain complex models to non-quants). Comfortable working in a fast-paced work environment. Work hours will be aligned to APAC Markets.

Dear Candidate, Greetings from Global Healthcare Billing Partners Pvt Ltd! We are pleased to inform you about Opening with the Global Healthcare for the profile of CHARGE ENTRY &PAYMENT POSTING Experience : 0.6Year - 4 Years Qualification : Any Graduate Essential Requirement :- Associate should have worked Experience in Charge Entry & Payment Posting with good knowledge of medical billing process. Location: Velachery Shift: Day Contact Name : MALINI HR Contact Details - 9003239650 / 8925808598 NOTE : (only Medical billing experience are eligible) Regards GLOBAL MALINI HR 90032 39650

ONLY IMMEDIATE JOINERS: Role & responsibilities Design, train, and deliver data science solutions using all modalities (tabular, text, image) Working hands on advanced analytics projects using python Mentor and work with a team of data scientists and data engineer to build advanced analytical solutions for clients Analyse experimental results, iterate, and refine models to create significant business impact Understanding and formulating the business problem into analytics framework Managing stakeholders, and communicating insights to business and technical teams Preferred candidate profile Mandatory: Time Series Forecasting, Demand Forecasting, Python, Pricing Analytics Customer and Marketing Analytics Pricing and Promotion Analytics Supply Chain Analytics Demand Forecasting / Production Planning / Procurement / Inventory Planning / Logistics Digital Analytics Predictive Maintenance / Predictive Quality In-depth understanding of various machine learning algorithms Ability to write robust codes in Python and familiarity with standard machine learning libraries is a plus Excellent communication and interpersonal skills to interact with internal and external stakeholders Good team player, self-motivated, able to ideate and work on various initiatives Perks and benefits

Roles & Responsibilities: Lead end-to-end development of demand forecasting models using classical time series (ARIMA, Exponential Smoothing), machine learning, and demand sensing techniques using market intelligence and historical sales data. Design and implement mathematical optimization solutions for production planning, scheduling and network optimization across manufacturing and distribution points. Work directly with supply chain leaders to translate business problems into quantitative models and deliver measurable improvements in service levels, cost, and efficiency. Deploy and maintain solutions in production environments, collaborating with engineering and business intelligence teams. Quantify business impact (e.g. xx% reduction in stockouts, xx% reduction in idle stock). Technical & Functional Skills: 6+ years of experience in demand forecasting and supply chain optimization in manufacturing or pharma domain. Strong demand forecasting expertise- Time series, machine learning and deep learning models. Strong programming in Python, SQL; familiarity with GCP or Azure. Deep knowledge of supply chain processes - production planning, inventory management, and logistics. Experience with simulation tools (e.g. Arena) is a plus. Ability to communicate complex models to non-technical stakeholders and influence decision-making. Good to have Expertise in solvers (e.g. Gurobi, CPLEX/ILOG, Hexaly) for MILP and Constraint-based optimization. About the Department | Digital Process and Excellence (DPEx): Our digital transformation journey is led by the DPEx team and is structured along the lines of Digitalize the Core and Transform with Digital. With a mandate to ensure continuous process improvement and drive patient centric innovation, it spans all functions and operations. In other words, you could be working on projects to expedite research outcomes one day, designing customer engagement platforms the next and simplifying warehouse processes the third. Some its priorities are: Reimagine Dr. Reddy’s as a ‘platform-based’ organization. Create Data as an asset that brings competitive advantage and business impact. Create Digital solutions that make the lives of our patients and customers easier and better.

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Data Scientist Location: Bangalore Reporting to: Senior Manager Purpose of the role The Global Brand Analytics Team at Anheuser-Busch InBev (AB InBev) is tasked with helping strengthen AB InBev’s brands across the globe. The solutions we provide aim to extract insights and give guidance on actionable from all our brand related data. The derived data-driven insights play a pivotal role in empowering our Marketing teams to make well-informed decisions backed by cutting edge modelling techniques and thorough analysis. Key tasks & accountabilities Execute coding skills to develop ML/time-series models. Focus on developing end-to-end analytical solution and present them to business partners/stakeholders. Should have consultative mindset to come up with solutions that can be easily understood and interpreted by business users. Research on the newer technologies and algorithms, to provide better solutions to the current problems. Interact and manage expectations of multiple stakeholders, building compelling narratives and help drive value for businesses by helping them strengthen brands on ground. Qualifications, Experience, Skills Level Of Educational Attainment Required Degree in business analytics / data science / statistics / economics and / or degree in Engineering, Mathematics or Computer Science. Previous Work Experience Minimum 3 years of experience, 2 years in to Data Science must. Hands-on experience in implementation of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques) and time-series algorithms (e.g. ARIMA, ARIMAX, UCM, Holt-Winters and others). Strong programming skills with working knowledge of SQL, Python. Excellent problem-solving and analytical mindset. Strong communication and interpersonal skills. Strong story boarding skills. Preferred Skills Marketing Analytics background in FMCG And above all of this, an undying love for beer! We dream big to create future with more cheers.

We are currently seeking talented individuals for multiple openings in Payment Posting, Denial Specialist, and Demo & Charge Entry roles. Payment Posting Specialist (End-to-End Process) - 10 positions available Denial Specialist (End-to-End Process) - 10 positions available Demo & Charge Entry Specialist - 10 positions available We are looking for candidates who can join immediately.

Lead AI Engineer (GenAI & AI/ML Focus) Experience : 5+ years (with at least 1-2 years in GenAI/Agentic AI) About the Role We’re seeking a Lead AI Engineer to drive the design, development, and scaling of intelligent systems powered by Generative AI and Agentic AI architectures. You’ll play a central role in shaping the technical foundation of our AI solutions, guiding junior engineers, leading experiments, and taking end-to-end ownership of core components such as prompt infrastructure, model routing logic, RAG systems, and autonomous agents. This role blends deep hands-on engineering with architectural vision and technical leadership. If you’re someone who enjoys building fast, mentoring others, and solving tough AI problems across infrastructure, experimentation, and deployment, this role is for you. What You’ll Do Architect and implement LLM-based GenAI systems: prompt pipelines, retrieval flows, model selection, fallback mechanisms, prompt optimization, prompt versioning, modular prompts, and tool orchestration strategies Design and lead multi-agent systems with memory, tool-use, task adaptation, and inter-agent collaboration using frameworks like LangGraph, CrewAI, AutoGen, LangChain Architect, deploy, and continuously evolve retrieval-augmented generation (RAG) pipelines, handle model substitution, evaluation, prompt versioning, and runtime fallback strategies Drive the creation of internal prompt libraries, LLM orchestration logic, and evaluation harnesses Collaborate on fine-tuning, embedding optimization, and multi-model substitution workflows Collaborate on model evaluation, benchmarking, and agentic stress testing in production Own end-to-end AI applications involving image, text, tabular, and signal data, working with both unimodal and multi-modal inputs Develop solutions in computer vision (e.g., OCR, classification, object detection) and multi-modal AI (e.g., text + image pipelines) Design and evaluate statistical models and classical ML systems, including time-series forecasting and predictive analytics Lead development of signal processing or anomaly detection systems (e.g., for sensor, telemetry, or log data) Build & support cost-optimization, compliance, and monitoring in GenAI deployments Mentor and unblock junior AI engineers and interns through code reviews, architecture sessions, and contribute to team knowledge base and enforce internal best practices Work closely with product, data, and platform teams to bring AI prototypes to production Partner with Data, Product, and Platform teams to ship enterprise-grade AI modules Who Should Apply You are a builder with: Minimum qualification: Bachelor’s or Master’s degree Disciplines: Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Engineering, Physics, Statistics, Finance, Economics, or any other quantitative or computational field 5+ years of professional experience in AI/ML development (with 1-2+ years in GenAI or Agentic systems) Proven experience architecting and shipping real-world AI applications at scale Strong mentoring skills and a product-focused engineering mindset An interest in shaping the long-term AI strategy while delivering short-term wins Must-Have Skills Strong Python development skills with emphasis on modular, testable design Deep familiarity with LLM APIs, prompt frameworks (e.g., LangChain, LangGraph, CrewAI), and RAG pipelines Experience building systems for model selection, prompt fallback, tool orchestration, and versioning Familiarity with MLOps pipelines, ML monitoring, and model lifecycle management Experience in building and optimizing RAG architectures and vector database integrations Knowledge of model selection, fallbacks, prompt versioning, and task decomposition Strong grasp of autonomous agent design, reasoning, tool use, and multi-agent protocols Exposure to near real-time signal/voice processing, filtering, or event-based triggers (e.g., anomaly/event detection) Practical knowledge of statistical modeling, forecasting (ARIMA, Prophet, ML-based), or classical ML pipelines 5+ years in AI/ML engineering, including 1–2+ years working directly on GenAI/Agentic AI projects Preferred Skills Experience with multi-agent collaboration patterns (e.g., A2A, MCP) Deployment experience on GenAI platforms like OpenAI, Claude, Vertex AI, Amazon Bedrock, or Azure GenAI Familiarity with serverless deployment, egress handling, and LLM usage constraints Exposure to evaluation frameworks, benchmarking suites, or internal testing systems Experience integrating AI flows with external systems (BI tools, dashboards, APIs, automation platforms) Prior experience designing multi-modal pipelines combining vision, text, or sensor data Bonus / Good-to-Have Hands-on with fine-tuning workflows (LoRA, PEFT, etc.) Understanding of vector database internals and hybrid retrieval methods Familiarity with CV/multi-modal AI workflows using OpenCV, TorchVision, CLIP, BLIP, or related libraries Prior experience contributing to open-source GenAI libraries or leading internal tool development Why Join Us Help shape the next-gen AI stack from the ground up Work in a fast-moving environment with real ownership and autonomy Collaborate with a cross-disciplinary team at the cutting edge of GenAI and agentic systems Be part of an organization that values experimentation, modularity, and long-term impact Interested candidates can share the CV on shikha.rana@antiersolutions.com

Company: Aiventory (A unit of Jazzoa Services OPC Private Limited) Location: Remote Stipend: ₹3,000 – ₹5,000/month Duration: 3 to 6 months Start Date: Immediate About Us: Aiventory is an AI-powered inventory management platform built specifically for India's Kirana stores and small retail businesses. We're on a mission to bring cutting-edge technology to the underserved sectors of India’s supply chain. We are currently seeking a passionate AI/ML Intern to join our product team and work closely on real-world machine learning applications like demand forecasting, anomaly detection, and computer vision for inventory intelligence. What You'll Work On: Building and training ML models (LSTM, ARIMA, Isolation Forest, etc.) Assisting in real-time prediction engine development for stock trends Image recognition using OpenCV or TensorFlow (barcode/label detection) Data preprocessing and feature engineering for retail datasets Supporting our AI roadmap across backend services You Should Know (at least some of): Python, Pandas, NumPy, Scikit-learn TensorFlow / PyTorch / OpenCV Time Series Forecasting models (ARIMA, LSTM) Basics of SQL or MongoDB Git and version control practices Bonus (Not Mandatory): Experience with retail or inventory datasets Worked on any personal ML projects or GitHub repos Familiarity with cloud (AWS, GCP) or Docker What You’ll Gain: Hands-on experience building real-world AI applications Certificate & Letter of Recommendation Potential for PPO (Pre-Placement Offer) based on performance Opportunity to work directly with the founding team and AI product manager

Design & implement plans, procedures & Processes Oversee daily operations of plants & the work of executives (Operations, maintenance, QA. HR) Evaluate performance by analyzing & interpreting data & metrics Assist CEO in new business developments Required Candidate profile Proven experience as Chief Operating Officer or relevant role Understanding of business functions such as operations, maintenance, HR & QA Expertise in designing systems & procedures Strategic Planner

Position Summary We are seeking a highly motivated and analytical Quant Analyst to join Futures First. The role involves supporting development and execution of quantitative strategies across financial markets. Job Profile Statistical Arbitrage & Strategy Development Design and implement pairs, mean-reversion, and relative value strategies in fixed income (govvies, corporate bonds, IRS). Apply cointegration tests (Engle-Granger, Johansen), Kalman filters, and machine learning techniques for signal generation. Optimize execution using transaction cost analysis (TCA). Correlation & Volatility Analysis Model dynamic correlations between bonds, rates, and macro variables using PCA, copulas, and rolling regressions. Forecast yield curve volatility using GARCH, stochastic volatility models, and implied-vol surfaces for swaptions. Identify regime shifts (e.g., monetary policy impacts) and adjust strategies accordingly. Seasonality & Pattern Recognition Analyse calendar effects (quarter-end rebalancing, liquidity patterns) in sovereign bond futures and repo markets. Develop time-series models (SARIMA, Fourier transforms) to detect cyclical trends. Back testing & Automation Build Python-based back testing frameworks (Backtrader, Qlib) to validate strategies. Automate Excel-based reporting (VBA, xlwings) for P&L attribution and risk dashboards. Integrate Bloomberg/Refinitiv APIs for real-time data feeds. Requirements Education Qualifications B.Tech Work Experience 0-3 years Skill Set Must have: Strong grasp of probability theory, stochastic calculus (Ito’s Lemma, SDEs), and time-series econometrics (ARIMA, VAR, GARCH). Must have: Expertise in linear algebra (PCA, eigenvalue decomposition), numerical methods (Monte Carlo, PDE solvers), and optimization techniques. Preferred: Knowledge of Bayesian statistics, Markov Chain Monte Carlo (MCMC), and machine learning (supervised/unsupervised learning) Libraries: NumPy, Pandas, statsmodels, scikit-learn, arch (GARCH models). Back testing: Backtrader, Zipline, or custom event-driven frameworks. Data handling: SQL, Dask (for large datasets). Power Query, pivot tables, Bloomberg Excel functions (BDP, BDH). VBA scripting for various tools and automation. Experience with C++/Java (low-latency systems), QuantLib (fixed income pricing), or R (statistical l). Yield curve modelling (Nelson-Siegel, Svensson), duration/convexity, OIS pricing. Credit spreads, CDS pricing, and bond-CDS basis arbitrage. Familiarity with VaR, CVaR, stress testing, and liquidity risk metrics. Understanding of CCIL, NDS-OM (Indian market infrastructure). Ability to translate intuition and patterns into quant models. Strong problem-solving and communication skills (must explain complex models to non-quants). Comfortable working in a fast-paced work environment. Location: Gurugram, Work hours will be aligned to APAC Markets.

Immediate DS Role Requirements – Key Skillset Must have supply chain experience with ML, especially inDemand Planning andRetail Merchandise Financial Planning Strong expertise inTime Series Forecasting using: Statistical models:ARIMA,Exponential Smoothing,Prophet ML models:XGBoost,LightGBM, etc. Minimum1 year of hands-on o9 platform experience Proficient inPython/R and relevant data science libraries Experience in buildingend-to-end ML pipelines for forecasting Strong understanding ofdemand drivers and retail planning cycles Excellent communication and cross-functional collaboration skills Experience required: 6+ years for Architects

We are looking for a Data Scientist to help us gain useful insight out of raw data. Data Scientist responsibilities include working with the data science team, planning projects and building analytics models. You should have a strong problem-solving ability and a knack for statistical analysis. If you’re also able to align our data products with our business goals, we’d like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data. Key Responsibilities ● Responsible for overseeing the data scientists team and data specialists ● Teach, lead, and counsel colleagues on new techniques or solutions ● Collaborate with data and software engineers to enable deployment of sciences and technologies that will scale across the company’s ecosystem ● Responsible for the conception, planning, and prioritizing of data projects ● Responsible for building analytic systems and predictive models as well as experimenting with new models and techniques ● Ensure that data projects align with organizational goals Minimum Qualification ● Master's degree in Computer Science, Operations Research, Econometrics, Statistics or related technical field ● 3+ years of experience solving analytical problems using quantitative approaches ● Experience communicating quantitative analysis results ● Knowledge with relational databases and SQL ● Development experience in any scripting language (PHP, Python, Perl, etc.) ● Knowledge of statistics (e.g., hypothesis testing, regressions) ● Experience manipulating data sets through statistical software (ex. R, SAS) or other methods Technical Skills - Must have – ● Programming – Python (Preferred) / R ● ML Models – i. Regression – Linear, Logistic, Multinomial, Mixed effect ● Classification – Bagging & Boosting (Random Forest), Decision tree, SVM ● Clustering – K-Means, hierarchical, DB-Scan ● Time series – ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS (VAR), UCM ● Neural Networks (Deep learning), Naive Bayes ● Excel and SQL ● Dimensionality Reduction – PCA, SVD etc. ● Optimization Techniques – Linear programming, Gradient Descent, Genetic Algorithm ● Cloud – Understanding of Azure / AWS offerings, Setting up ML pipeline of cloud Good to have – ● Visualization – Tableau / Power BI / Looker / QlikView ● Data management – HDFS, Spark, Advanced Excel ● Agile Tools – Azure DevOps, JIRA ● Pyspark ● Big Data/Hive Database ● IDE: Pycharm Show more Show less

Location Gurugram, India Share Position Summary We are seeking a highly motivated and analytical Quant Analyst to join Futures First. The role involves supporting development and execution of quantitative strategies across financial markets. Job Profile Statistical Arbitrage & Strategy Development Design and implement pairs, mean-reversion, and relative value strategies in fixed income (govvies, corporate bonds, IRS). Apply cointegration tests (Engle-Granger, Johansen), Kalman filters, and machine learning techniques for signal generation. Optimize execution using transaction cost analysis (TCA). Correlation & Volatility Analysis Model dynamic correlations between bonds, rates, and macro variables using PCA, copulas, and rolling regressions. Forecast yield curve volatility using GARCH, stochastic volatility models, and implied-vol surfaces for swaptions. Identify regime shifts (e.g., monetary policy impacts) and adjust strategies accordingly. Seasonality & Pattern Recognition Analyse calendar effects (quarter-end rebalancing, liquidity patterns) in sovereign bond futures and repo markets. Develop time-series models (SARIMA, Fourier transforms) to detect cyclical trends. Back testing & Automation Build Python-based back testing frameworks (Backtrader, Qlib) to validate strategies. Automate Excel-based reporting (VBA, xlwings) for P&L attribution and risk dashboards. Integrate Bloomberg/Refinitiv APIs for real-time data feeds. Requirements Education Qualifications B.Tech Work Experience 0-3 years Skill Set Must have: Strong grasp of probability theory, stochastic calculus (Ito’s Lemma, SDEs), and time-series econometrics (ARIMA, VAR, GARCH). Must have: Expertise in linear algebra (PCA, eigenvalue decomposition), numerical methods (Monte Carlo, PDE solvers), and optimization techniques. Preferred: Knowledge of Bayesian statistics, Markov Chain Monte Carlo (MCMC), and machine learning (supervised/unsupervised learning) Libraries: NumPy, Pandas, statsmodels, scikit-learn, arch (GARCH models). Back testing: Backtrader, Zipline, or custom event-driven frameworks. Data handling: SQL, Dask (for large datasets). Power Query, pivot tables, Bloomberg Excel functions (BDP, BDH). VBA scripting for various tools and automation. Experience with C++/Java (low-latency systems), QuantLib (fixed income pricing), or R (statistical l). Yield curve modelling (Nelson-Siegel, Svensson), duration/convexity, OIS pricing. Credit spreads, CDS pricing, and bond-CDS basis arbitrage. Familiarity with VaR, CVaR, stress testing, and liquidity risk metrics. Understanding of CCIL, NDS-OM (Indian market infrastructure). Ability to translate intuition and patterns into quant models. Strong problem-solving and communication skills (must explain complex models to non-quants). Comfortable working in a fast-paced work environment. Location: Gurugram, Work hours will be aligned to APAC Markets.

Job Title: Data Scientist – Financial Analytics Location: Onsite – Okhla Vihar, New Delhi Experience: 2-3 Years About the Role: We are seeking a passionate and results-driven Data Scientist to join our analytics team at our Okhla Vihar office. This role is ideal for someone with 2–3 years of hands-on experience in applying data science techniques to financial datasets, with a strong foundation in Python, SQL, and time series forecasting. You will play a key role in analyzing complex financial data, building predictive models, and delivering actionable insights to support critical business decisions. Key Responsibilities: Analyze large volumes of structured and unstructured financial data to extract meaningful insights. Build and evaluate predictive models using machine learning techniques (e.g., Scikit learn). Perform time series analysis and forecasting for financial indicators (e.g., market trends, portfolio performance, cash flows). Design and implement robust feature engineering pipelines to improve model accuracy. Develop risk modeling frameworks to assess financial risk (e.g., credit risk, market risk). Write complex and optimized SQL queries for data extraction and transformation. Leverage Python libraries like Pandas, NumPy, and SciPy for data preprocessing and manipulation. Create clear and insightful data visualizations using Matplotlib, Seaborn, or Plotly to communicate findings. Work closely with finance and strategy teams to translate business needs into data-driven solutions. Monitor and fine-tune models in production to ensure continued relevance and accuracy. Document models, assumptions, and methodologies for auditability and reproducibility. Required Skills & Experience: 2–3 years of experience as a Data Scientist, preferably in a financial services or fintech environment. Proficient in Python (Pandas, Scikit-learn, NumPy, SciPy, etc.). Strong experience in SQL for querying large datasets. Deep understanding of time series modeling (ARIMA, SARIMA, Prophet, etc.). Experience with feature selection, feature transformation, and data imputation techniques. Solid understanding of financial concepts such as ROI, risk/return, volatility, portfolio analysis, and pricing models. Exposure to risk modeling (credit scoring, stress testing, scenario analysis). Strong analytical and problem-solving skills with attention to detail. Experience with data visualization tools – Matplotlib, Seaborn, or Plotly. Ability to interpret model outputs and convey findings to both technical and non technical stakeholders. Excellent communication and collaboration skills. Preferred Qualifications: Bachelor’s or Master’s degree in Data Science, Statistics, Finance, Economics, Computer Science, or a related field. Experience working with financial time series datasets (e.g., stock prices, balance sheets, trading data). Understanding of regulatory frameworks and compliance in financial analytics. Familiarity with cloud platforms (AWS, GCP) is a plus. Experience working in agile teams. What We Offer: Competitive salary and performance incentives Onsite role at a modern office located in Okhla Vihar, New Delhi A collaborative and high-growth work environment Opportunities to work on real-world financial data challenges Exposure to cross-functional teams in finance, technology, and business strategy How to Apply: If you’re excited to work at the intersection of data science and finance, and want to be part of a dynamic team solving real-world financial challenges, we’d love to hear from you. Please send your resume, portfolio (if applicable), and a brief note about why you're a great fit to [your email/HR contact here]. Job Type: Full-time Pay: ₹600,000.00 - ₹1,200,000.00 per year Schedule: Morning shift Work Location: In person

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Manager- GBS Commercial Location: Bangalore Reporting to: Senior Manager - GBS Commercial Purpose of the role This role sits at the intersection of data science and revenue growth strategy, focused on developing advanced analytical solutions to optimize pricing, trade promotions, and product mix. The candidate will lead the end-to-end design, deployment, and automation of machine learning models and statistical frameworks that support commercial decision-making, predictive scenario planning, and real-time performance tracking. By leveraging internal and external data sources—including transactional, market, and customer-level data—this role will deliver insights into price elasticity, promotional lift, channel efficiency, and category dynamics. The goal is to drive measurable improvements in gross margin, ROI on trade spend, and volume growth through data-informed strategies. Key tasks & accountabilities Design and implement price elasticity models using linear regression, log-log models, and hierarchical Bayesian frameworks to understand consumer response to pricing changes across channels and segments. Build uplift models (e.g., Causal Forests, XGBoost for treatment effect) to evaluate promotional effectiveness and isolate true incremental sales vs. base volume. Develop demand forecasting models using ARIMA, SARIMAX, and Prophet, integrating external factors such as seasonality, promotions, and competitor activity. time-series clustering and k-means segmentation to group SKUs, customers, and geographies for targeted pricing and promotion strategies. Construct assortment optimization models using conjoint analysis, choice modeling, and market basket analysis to support category planning and shelf optimization. Use Monte Carlo simulations and what-if scenario modeling to assess revenue impact under varying pricing, promo, and mix conditions. Conduct hypothesis testing (t-tests, ANOVA, chi-square) to evaluate statistical significance of pricing and promotional changes. Create LTV (lifetime value) and customer churn models to prioritize trade investment decisions and drive customer retention strategies. Integrate Nielsen, IRI, and internal POS data to build unified datasets for modeling and advanced analytics in SQL, Python (pandas, statsmodels, scikit-learn), and Azure Databricks environments. Automate reporting processes and real-time dashboards for price pack architecture (PPA), promotion performance tracking, and margin simulation using advanced Excel and Python. Lead post-event analytics using pre/post experimental designs, including difference-in-differences (DiD) methods to evaluate business interventions. Collaborate with Revenue Management, Finance, and Sales leaders to convert insights into pricing corridors, discount policies, and promotional guardrails. Translate complex statistical outputs into clear, executive-ready insights with actionable recommendations for business impact. Continuously refine model performance through feature engineering, model validation, and hyperparameter tuning to ensure accuracy and scalability. Provide mentorship to junior analysts, enhancing their skills in modeling, statistics, and commercial storytelling. Maintain documentation of model assumptions, business rules, and statistical parameters to ensure transparency and reproducibility. Other Competencies Required Presentation Skills: Effectively presenting findings and insights to stakeholders and senior leadership to drive informed decision-making. Collaboration: Working closely with cross-functional teams, including marketing, sales, and product development, to implement insights-driven strategies. Continuous Improvement: Actively seeking opportunities to enhance reporting processes and insights generation to maintain relevance and impact in a dynamic market environment. Data Scope Management: Managing the scope of data analysis, ensuring it aligns with the business objectives and insights goals. Act as a steadfast advisor to leadership, offering expert guidance on harnessing data to drive business outcomes and optimize customer experience initiatives. Serve as a catalyst for change by advocating for data-driven decision-making and cultivating a culture of continuous improvement rooted in insights gleaned from analysis. Continuously evaluate and refine reporting processes to ensure the delivery of timely, relevant, and impactful insights to leadership stakeholders while fostering an environment of ownership, collaboration, and mentorship within the team. Technical Skills - Must Have Data Manipulation & Analysis: Advanced proficiency in SQL, Python (Pandas, NumPy), and Excel for structured data processing. Data Visualization: Expertise in Power BI and Tableau for building interactive dashboards and performance tracking tools. Modeling & Analytics: Hands-on experience with regression analysis, time series forecasting, and ML models using scikit-learn or XGBoost. Data Engineering Fundamentals: Knowledge of data pipelines, ETL processes, and integration of internal/external datasets for analytical readiness. Proficient in Power BI, Advanced MS Excel (Pivots, calculated fields, Conditional formatting, charts, dropdown lists, etc.), MS PowerPoint SQL & Python. Business Environment Work closely with Zone Revenue Management teams. Work in a fast-paced environment. Provide proactive communication to the stakeholders. This is an offshore role and requires comfort with working in a virtual environment. GCC is referred to as the offshore location. The role requires working in a collaborative manner with Zone/country business heads and GCC commercial teams. Summarize insights and recommendations to be presented back to the business. Continuously improve, automate, and optimize the process. Geographical Scope: Global 3. Qualifications, Experience, Skills Level Of Educational Attainment Required Bachelor or Post-Graduate in the field of Business & Marketing, Engineering/Solution, or other equivalent degree or equivalent work experience. Previous Work Experience 5-8 years of experience in the Retail/CPG domain. Extensive experience solving business problems using quantitative approaches. Comfort with extracting, manipulating, and analyzing complex, high volume, high dimensionality data from varying sources. And above all of this, an undying love for beer! We dream big to create future with more cheer. Show more Show less

At o9 Solutions, our mission is clear: be the Most Valuable Platform (MVP) for enterprises. With our AI-driven platform — the o9 Digital Brain — we integrate global enterprises’ siloed planning capabilities, helping them capture millions and, in some cases, billions of dollars in value leakage. But our impact doesn’t stop there. Businesses that plan better and faster also reduce waste, which drives better outcomes for the planet, too. We're on the lookout for the brightest, most committed individuals to join us on our mission. Along the journey, we’ll provide you with a nurturing environment where you can be part of something truly extraordinary and make a real difference for companies and the plane t What you’ll do for us: Apply a variety of machine learning techniques (clustering, regression, ensemble learning, neural nets, time series, optimizations etc.) to their real-world advantages/drawbacks Develop and/or optimize models for demand sensing/forecasting, optimization (Heuristic, LP, GA etc), Anomaly detection, Simulation and stochastic models, Market Intelligence etc. Use latest advancements in AI/ML to solve business problems Analyze problems by synthesizing complex information, evaluating alternate methods, and articulating the result with the relevant assumptions/reasons Application of common business metrics (Forecast Accuracy, Bias, MAPE) and the ability to generate new ones as needed. Develop or optimize modules to call web services for real time integration with externa systems Work collaboratively with Clients, Project Management, Solution Architects, Consultants and Data Engineers to ensure successful delivery of o9 projects What you’ll have: Experience: 4+ Years of experience in time series forecasting in scale using heuristic-based hierarchical best-fit models using algorithms like exponential smoothing, ARIMA, prophet and custom parameter tuning. Experience in applied analytical methods in the field of Supply chain and planning, like demand planning, supply planning, market intelligence, optimal assortments/pricing/inventory etc. Should be from a statistical background. Education: Bachelors Degree in Computer Science, Mathematics, Statistics, Economics, Engineering or related field Languages: Python and/or R for Data Science Skills: Deep Knowledge of statistical and machine learning algorithms, building scalable ML frameworks, identifying and collecting relevant input data, feature engineering, tuning, and testing. Characteristics: Independent thinkers Strong presentation and communications skills We really value team spirit: Transparency and frequent communication is key. At o9, this is not limited by hierarchy, distance, or function. Nice to have: Experience with SQL, databases and ETL tools or similar is optional but preferred Exposure to distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, or related Big Data technologies Experience with Deep Learning frameworks such as Keras, Tensorflow or PyTorch is preferable Experience in implementing planning applications will be a plus Understanding of Supply Chain Concepts will be preferable Masters Degree in Computer Science, Applied Mathematics, Statistics, Engineering, Business Analytics, Operations, or related field What we’ll do for you Competitive salary with stock options to eligible candidates Flat organization: With a very strong entrepreneurial culture (and no corporate politics) Great people and unlimited fun at work Possibility to make a difference in a scale-up environment. Opportunity to travel onsite in specific phases depending on project requirements. Support network: Work with a team you can learn from everyday. Diversity: We pride ourselves on our international working environment. Work-Life Balance: https://youtu.be/IHSZeUPATBA?feature=shared Feel part of A team: https://youtu.be/QbjtgaCyhes?feature=shared How the process works Apply by clicking the button below You’ll be contacted by our recruiter, who’ll fill you in on all things at o9, give you some background about the role and get to know you. They’ll contact you either via video call or phone call - whatever you prefer. During the interview phase, you will meet with technical panels for 60 minutes. The recruiter will contact you after the interview to let you know if we’d like to progress your application. We will have 2 rounds of Technical discussion followed by a Hiring Manager discussion. Our recruiter will let you know if you’re the successful candidate. Good luck! More about us … With the latest increase in our valuation from $2.7B to $3.7B despite challenging global macroeconomic conditions, o9 Solutions is one of the fastest-growing technology companies in the world today. Our mission is to digitally transform planning and decision-making for the enterprise and the planet. Our culture is high-energy and drives us to aim 10x in everything we do. Our platform, the o9 Digital Brain, is the premier AI-powered, cloud-native platform driving the digital transformations of major global enterprises including Google, Walmart, ABInBev, Starbucks and many others. Our headquarters are located in Dallas, with offices in Amsterdam, Paris, London, Barcelona, Madrid, Sao Paolo, Bengaluru, Tokyo, Seoul, Milan, Stockholm, Sydney, Shanghai, Singapore an d Munich. o9 is an equal opportunity employer and seeks applicants of diverse backgrounds and hires without regard to race, colour, gender, religion, national origin, citizenship, age, sexual orientation or any other characteristic protected by law Show more Show less

Dear Candidate, Greetings from Global Healthcare Billing Partners Pvt Ltd! We are pleased to inform you about Opening with the Global Healthcare for the profile of CHARGE ENTRY &PAYMENT POSTING!!! Experience : 1Years - 6 Years Qualification : Any Graduate Notice: Immediate Joiner. Essential Requirement :- Associate should have worked Experience in Charge entry & Payment Posting with good knowledge of medical billing process. Location: Velachery Shift: Day Mode of interview: Direct walk-in [Interview Call Letter is MANDATORY so please Reach out before coming directly.] Interview timing (11.30am-3pm) Contact Name : KAYAL HR Contact Details - 8925808597 (Call or Whatsapp) NOTE : (only Medical billing experience with 1Yrs are eligible) Regards KAYAL HR GLOBAL

Job Summary: We are looking for a highly skilled Data Scientist with deep expertise in time series forecasting, particularly in demand forecasting and customer lifecycle analytics (CLV). The ideal candidate will be proficient in Python or PySpark, have hands-on experience with tools like Prophet and ARIMA, and be comfortable working in Databricks environments. Familiarity with classic ML models and optimization techniques is a plus. Key Responsibilities • Develop, deploy, and maintain time series forecasting models (Prophet, ARIMA, etc.) for demand forecasting and customer behavior modeling. • Design and implement Customer Lifetime Value (CLV) models to drive customer retention and engagement strategies. • Process and analyze large datasets using PySpark or Python (Pandas). • Partner with cross-functional teams to identify business needs and translate them into data science solutions. • Leverage classic ML techniques (classification, regression) and boosting algorithms (e.g., XGBoost, LightGBM) to support broader analytics use cases. • Use Databricks for collaborative development, data pipelines, and model orchestration. • Apply optimization techniques where relevant to improve forecast accuracy and business decision-making. • Present actionable insights and communicate model results effectively to technical and non-technical stakeholders. Required Qualifications • Strong experience in Time Series Forecasting, with hands-on knowledge of Prophet, ARIMA, or equivalent – Mandatory. • Proven track record in Demand Forecasting – Highly Preferred. • Experience in modeling Customer Lifecycle Value (CLV) or similar customer analytics use cases – Highly Preferred. • Proficiency in Python (Pandas) or PySpark – Mandatory. • Experience with Databricks – Mandatory. • Solid foundation in statistics, predictive modeling, and machine learning. Show more Show less