244 Arima Jobs - Page 8

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

We are seeking a data scientist with strong technical expertise in machine learning and statistical analysis to develop and deploy impactful data solutions. The role involves designing and implementing predictive models (e.g., regression, classification, NLP, time series), collaborating with stakeholders to solve business problems, and driving strategic decisions through experimentation and data-driven insights Job Description: Key responsibilities: 1. Modeling & Machine Learning Design and implement robust machine learning solutions (e.g., regression, classification, NLP, time series, recommendation systems). Evaluate and tune models using appropriate metrics (AUC, RMSE, precision/recall, etc.). Work on feature engineering, model interpretability, and performance optimization. 2. Data-Driven Business Strategy Partner with stakeholders to identify key opportunities where data science can drive business value. Translate business problems into data science projects with clearly defined deliverables and success metrics. Provide actionable recommendations based on data analysis and model outputs. 3. Analytics and Experimentation Conduct deep-dive exploratory analysis to uncover trends and insights. Apply statistical methods to test hypotheses, forecast trends, and measure campaign effectiveness Design and analyze A/B tests and other experiments to support product and marketing decisions. Automate data pipelines and dashboards for ongoing monitoring of model and business performance. Technical Skills: Languages: Proficient in Python, MySQL. Libraries/Frameworks: scikit-learn, Pandas, NumPy, Time series, ARIMA, Bayesian model, Market Mix model, Regression, XGBoost, LightGBM, TensorFlow, PyTorch. Statistical Method: Proficient in statistical techniques such as hypothesis testing, regression analysis, time-series analysis Databases : PostgreSQL, BigQuery, MySQL. Visualization: Plotly, Seaborn, Matplotlib. Deployment: Experience in Gitlab, CI/CD pipelines(Good to have). Cloud Platforms: Familiarity with AWS, GCP, or Azure services(Good to have). Location: Chennai Brand: Paragon Time Type: Full time Contract Type: Permanent

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

We are seeking a data scientist with strong technical expertise in machine learning and statistical analysis to develop and deploy impactful data solutions. The role involves designing and implementing predictive models (e.g., regression, classification, NLP, time series), collaborating with stakeholders to solve business problems, and driving strategic decisions through experimentation and data-driven insights Job Description: Key responsibilities: Modeling & Machine Learning Design and implement robust machine learning solutions (e.g., regression, classification, NLP, time series, recommendation systems). Evaluate and tune models using appropriate metrics (AUC, RMSE, precision/recall, etc.). Work on feature engineering, model interpretability, and performance optimization. Data-Driven Business Strategy Partner with stakeholders to identify key opportunities where data science can drive business value. Translate business problems into data science projects with clearly defined deliverables and success metrics. Provide actionable recommendations based on data analysis and model outputs. Analytics and Experimentation Conduct deep-dive exploratory analysis to uncover trends and insights. Apply statistical methods to test hypotheses, forecast trends, and measure campaign effectiveness Design and analyze A/B tests and other experiments to support product and marketing decisions. Automate data pipelines and dashboards for ongoing monitoring of model and business performance. Technical Skills: Languages: Proficient in Python, MySQL. Libraries/Frameworks: scikit-learn, Pandas, NumPy, Time series, ARIMA, Bayesian model, Market Mix model, Regression, XGBoost, LightGBM, TensorFlow, PyTorch. Statistical Method: Proficient in statistical techniques such as hypothesis testing, regression analysis, time-series analysis Databases : PostgreSQL, BigQuery, MySQL. Visualization: Plotly, Seaborn, Matplotlib. Deployment: Experience in Gitlab, CI/CD pipelines(Good to have). Cloud Platforms: Familiarity with AWS, GCP, or Azure services(Good to have). Location: Chennai Brand: Paragon Time Type: Full time Contract Type: Permanent Show more Show less

About Northern Trust Northern Trust, a Fortune 500 company, is a globally recognized, award-winning financial institution that has been in continuous operation since 1889. Northern Trust is proud to provide innovative financial services and guidance to the world’s most successful individuals, families, and institutions by remaining true to our enduring principles of service, expertise, and integrity. With more than 130 years of financial experience and over 22,000 partners, we serve the world’s most sophisticated clients using leading technology and exceptional service. Job Summary Job Function: Model Development Associate Consultant/Consultant, is a key member of the Risk Analytics and Data Service Team and Responsible for acting as an individual contributor in the development and maintenance of high quality risk analytics. Resolves complex issues in Credit Risk/ PPNR modelling and measuring risk, enhancement in Credit Risk/ PPNR methodologies or other aspects of risk measurement. Job title: Associate Consultant/Consultant Location: Bangalore Experience: 4-8 years of relevant experience Major Duties Responsible for Development of CCAR models (PD/EAD/LGD) , CECL models (PD/EAD/LGD) and Basel models (PD/EAD/LGD). Also for PPNR model development for Non-Interest Income, Net Interest Income, Expense, Deposit, Balance models. Ensures regular production of analytical work.. Collaborates with regulators, Audit Services, and other independent reviewers. Evaluates existing framework in relation to corporate objectives and industry leading practices. Assesses development needs and manages process to achieve desired future state. Supports stress testing, capital quantification and/or internal capital allocation methodologies. Ensures that modelling approaches meet both internal corporate needs and regulatory requirements related to prevailing regulatory guidance. Provides technical/theoretical inputs to resolve risk issues and enhance overall risk framework. Works with other risk or business unit teams to ensure that risk management policies/processes and quantitative modelling approaches are consistent. Operates independently; has knowledge of banking balance sheets and income statements. Conducts analysis, independently ensuring accuracy and completeness. Responsible for interaction with different committees and/or senior management. Qualification Master in Statistics/ Economics/Mathematics/advanced degree in quant area Or B.tech. From tier 1 college with MBA in related field Skills Required Strong BASEL, CCAR and DFAST, SR-11/7 understanding. Strong regulatory understanding 2+ years of hands on model building experience in Credit Risk / PPNR Strong conceptual and technical knowledge of risk concepts and quantitative modelling techniques including familiarity with statistical concepts used in stress testing Strong in quantitative skills – experience in model validation a plus Experience in R, SAS, Matlab, advanced Excel techniques and VBA programming. SAS is preferred Strong Experience in building linear regression models, Nonlinear regression, time series modeling (ARIMA, AR, VAR, MA ) and stochastic process Strong organizational and interpersonal skills Excellent verbal and written communication skills (English) Experience of working in a multi-cultural and global environment Related Industry qualification (e.g., CFA, FRM) a plus Working With Us As a Northern Trust partner, greater achievements await. You will be part of a flexible and collaborative work culture in an organization where financial strength and stability is an asset that emboldens us to explore new ideas. Movement within the organization is encouraged, senior leaders are accessible, and you can take pride in working for a company committed to assisting the communities we serve! Join a workplace with a greater purpose. We’d love to learn more about how your interests and experience could be a fit with one of the world’s most admired and sustainable companies! Build your career with us and apply today. Reasonable accommodation Northern Trust is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation for any part of the employment process, please email our HR Service Center at MyHRHelp@ntrs.com. We hope you’re excited about the role and the opportunity to work with us. We value an inclusive workplace and understand flexibility means different things to different people. Apply today and talk to us about your flexible working requirements and together we can achieve greater. For further information, and to apply, please visit our website via the “Apply” button below. Show more Show less

Job Description: Data Scientist - Forecasting We are seeking a highly analytical and experienced Data Scientist to join our Workforce Planning or Analytics team. The ideal candidate will focus on long-term forecasting for contact center operations, leveraging machine learning models and advanced analytics to drive data-informed decisions using Python, SQL and Power BI. You will play a critical role in projecting future contact volumes, resource requirements, and operational trends, directly supporting strategic planning and optimization efforts across the business. Key Responsibilities Analytics & Insights: Analyze historical trends and seasonality to make informed decisions. Apply machine learning and statistical techniques (e.g., ARIMA, Prophet, XGBoost, LSTM, etc.) to improve forecast accuracy over months and years. Conduct in-depth analysis using Excel or Python to identify key drivers of change in volume. Generate Forecast: Generate monthly forecasts for multiple lobs using machine learning models. Monitor and adjust forecasts based on trends, seasonality, and business updates. Forecast assessment: Evaluate forecast accuracy every month and present key findings. Monitor forecast performance, diagnose deviations, and continuously improve model performance using feedback loops and model validation. Stakeholder Collaboration: Present analytical findings and strategic recommendations to stakeholders, especially around critical days or events. Collaborate with cross-functional teams to understand business requirements and deliver analytical solutions Required Skills & Expertise Technical Skills: Proficiency in Excel, SQL and Python for advanced data analysis, data extraction and data manipulation Hands-on experience with data visualization tools (e.g., Tableau, Power BI) is a plus. Analytical Acumen: Advanced knowledge of Time Series forecasting techniques or Contact Center demand volume forecasting. Ability to work with large datasets and extract meaningful insights to generate forecasts Ability to work on ad-hoc requests to support business needs and derive actionable insights Problem-Solving & Communication: Strong problem-solving skills, with the ability to translate complex analytical findings into clear and actionable recommendations. Excellent communication and data storytelling skills; able to influence stakeholders using evidence-based insights Candidate Profile Educational Background: Bachelor’s/Master’s degree in Analytics, Data Science, Economics, Statistics, Engineering, or a related field. Professional Experience: At least 3-5 years of experience in the data analytics with good experience of Time Series Forecasting. Show more Show less

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: Analyst – Junior Data Scientist Location: Bangalore Reporting to: Manager Analytics Purpose of the role 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 Bachelor’s degree with minimum 2 years of Data Science experience 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 And above all of this, an undying love for beer! We dream big to create future with more cheers Show more Show less

Job Title: Data Scientist Location: Navi Mumbai Experience: 3-6 Years Duration: Fulltime 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

Description GlobalLogic seeking a highly analytical and detail-oriented MIS / Workforce Management (WFM) Team Manager to join our team. In this role, you will support operations through accurate reporting, data-driven insights, and efficient workforce planning. Requirements Minimum of 5 years of experience in MIS and/or Workforce Management. Strong background in handling invoicing within service-based environments. Advanced proficiency in Microsoft Excel, including formulas, pivot tables, and macros. Familiarity with Amazon Connect, Monte Carlo simulations, and forecasting models such as SARIMA/ARIMA. Understanding of billing models, specifically BE6. Experience with data visualization tools (e.g., Power BI, Tableau) is a plus. Exceptional attention to detail, with a strong analytical and problem-solving mindset. Excellent communication skills and proven ability to manage stakeholder expectations. Job responsibilities Lead the development and execution of MIS and WFM strategies to enhance operational reporting, forecasting, and efficiency. Design and maintain dashboards and reports using Excel, Power BI, or similar tools to provide actionable insights. Track key workforce metrics such as staffing levels, schedule adherence, and occupancy rates, and provide data-backed recommendations for optimization. Collaborate with internal stakeholders to collect invoice-related data, ensure billing accuracy, and manage timely invoice generation. Reconcile timesheets and billable hours with contract requirements and service level agreements What we offer Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally. Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today. Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way! High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do. About GlobalLogic GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services. Show more Show less

Job Title: Data Scientists Location: Navi Mumbai Duration: Fulltime Positions: Multiple We are looking for a highly skilled Data Scientists 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

Title : Senior Manager -Data Science, Machine Learning and GenAI Technical Leader Job Area: Information Technology Group, Information Technology Group > IT Management General Summary: Experience in engaging with business and technical stakeholders, understanding complex problem statements, and proposing value-driven Data Science & ML solutionsFunctional & technical leadership in developing data science roadmap and guiding the team with end-to-end delivery (design, development, maintenance, and optimization) of advanced analytical solutions with focus on process standardization and best practicesProactive in reaching out to wide variety of stakeholders for increasing the awareness of Data Science, ML and GenAI capabilities and identifying business value driven opportunitiesAnalyze the market and industry trends in the technology and proactively look for opportunities in bringing the best solutions 'Strong analytical skills with the ability to gather information from several sources and identify fundamental patterns/trends in dataConduct research, design statistical studies and develop solutionsDevelop Story Telling dashboards on analytics to assist business in decision makingImplement deep learning models for structured and unstructured data setsPerform Time Series Analysis and Forecast (ARIMA, Exponential Smoothing, VAR etc.)Implementation experience with identifying, prototyping, developing and delivering GenAI solutions using Industry standard RAG models and frameworksAbility to develop capabilities in Text Analytics ranging from Basic to Advanced (Topic Modelling, NLP)Experience with AWS suite of Data Science and ML toolsDevelops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, Catboost etc.) 'Experience with other cloud platforms (GCP and Azure)Understanding of Data Platforms and Data EngineeringExposure to ChatBot solutions and Automation technologies Minimum Qualifications: 7+ years of IT-related work experience with a Bachelor's degree. OR 9+ years of IT-related work experience without a Bachelors degree. 4+ years in a leadership role in projects/programs.

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 Locations: Mumbai/Pune/Noida/Bangalore/Jaipur/Hyderabad

Job Description: Forecasting Specialist with Expertise in Inventory Management We are looking for a Forecasting Specialist with a strong background in inventory management and data-driven demand forecasting . This role is focused on optimizing inventory levels and enhancing supply chain efficiency through advanced forecasting models and analytical tools. The ideal candidate will bring expertise in statistical forecasting, data analysis, and technical systems to improve retail inventory operations. Responsibilities Statistical Demand Forecasting : Utilize advanced statistical techniques (e.g., ARIMA , exponential smoothing , seasonal decomposition , regression models ) to create accurate demand forecasts and inventory plans. Inventory Optimization : Apply mathematical models like EOQ (Economic Order Quantity) , Safety Stock Calculation , and Replenishment Algorithms to optimize inventory levels and minimize holding costs. Data Analysis & Reporting : Extract and analyze large datasets from various sources, utilizing SQL and advanced analytics tools to forecast trends, detect anomalies, and ensure inventory alignment with demand. Forecasting Model Development : Continuously develop, refine, and evaluate statistical models to improve forecasting accuracy and adapt to changing consumer behavior. System Integration : Work with ERP systems (e.g., SAP , Oracle ) and integrate them with forecasting platforms (e.g., Demand Works , Forecast Pro ) to streamline inventory management processes and ensure real-time data synchronization. Automation and Scripting : Write Python or R scripts to automate data extraction, cleaning, analysis, and forecasting tasks. Data Visualization & Communication : Leverage tools like Power BI , Tableau , or Google Data Studio to build dashboards that present inventory insights and forecasting accuracy to stakeholders in an actionable format. Continuous Improvement : Apply machine learning techniques (e.g., regression models , decision trees , ensemble methods ) to enhance forecasting models and adapt to new retail trends. Key Technical Skills Statistical Tools & Forecasting : Expertise in R or Python for statistical analysis and time series forecasting. In-depth knowledge of forecasting techniques (ARIMA, Holt-Winters, Exponential Smoothing). Understanding of advanced regression and machine learning algorithms applied to demand prediction and trend analysis. SQL & Database Management Proficiency in writing complex SQL queries to extract and manipulate data from inventory and sales databases (MySQL, PostgreSQL, etc.). Experience working with relational databases and cloud-based solutions for inventory data management. Inventory Optimization Algorithms Advanced understanding of inventory models such as ABC Classification , Just-In-Time (JIT) , Reorder Point (ROP) , Safety Stock Optimization , and Vendor-Managed Inventory (VMI) . Ability to apply algorithms to dynamically adjust reorder quantities based on fluctuating demand. Data Visualization & Business Intelligence Expertise in data visualization tools like Power BI to present key performance metrics and inventory analytics to non-technical stakeholders. Ability to create interactive dashboards that display key inventory KPIs (e.g., stock levels, turnover rates, and demand forecasts). Automation & Scripting Proficient in Python (pandas, NumPy) or R for scripting and automating inventory analysis and forecasting processes. Experience with Jupyter Notebooks or RStudio for developing reproducible analysis workflows. Additional Skills Machine Learning (ML) : Knowledge of machine learning algorithms (e.g., XGBoost , Random Forests , Neural Networks ) for improving predictive accuracy in demand forecasting. Desired Qualifications Bachelor's degree in Statistics , Computer Science , Supply Chain Management , or a related field. Proven experience in a similar technical forecasting or inventory management role, preferably in a retail or e-commerce setting. Strong problem-solving skills and a keen attention to detail in data quality and accuracy. This is a high-impact, technical role where you will leverage your expertise in statistical forecasting , data analysis , and inventory optimization to drive significant improvements in retail inventory management systems. If you are passionate about using advanced data science techniques to solve complex supply chain problems, we encourage you to apply. Show more Show less

About The Role We are seeking a highly skilled and hands-on Senior Data Scientist with 7+ years of experience to lead the design and implementation of robust machine learning pipelines and drive data-driven decision making across the organization. This role requires a strategic thinker who can bridge the gap between complex data science concepts and practical business solutions, while ensuring model integrity, explainability, and compliance in production environments. As a Senior Data Scientist, you will have end-to-end ownership of the model life cycle, from data ingestion and feature engineering to model deployment, monitoring, and governance. Youll work closely with AI engineers, product teams, and stakeholders to deliver high-impact solutions that drive business value. Key Responsibilities Machine Learning & Predictive Modeling : Design and build sophisticated predictive models using Scikit-learn, XG Boost, LightGBM, and CatBoost for various use cases. Develop advanced forecasting models using Prophet, ARIMA, and neural forecasting techniques for time series analysis. Implement anomaly detection systems and risk scoring models for fraud detection and security applications Create recommendation systems and personalization algorithms using collaborative filtering and deep learning approaches AI Integration & Pipeline Development Collaborate with AI engineers to integrate traditional ML components into LangChain and LLM-driven intelligent systems Design hybrid architectures that combine classical ML with generative AI for enhanced business solutions Develop evaluation frameworks for comparing traditional ML and LLM based approaches Implement retrieval systems that enhance LLM performance with domain specific knowledge Model Lifecycle Management Automate comprehensive model lifecycle processes including training, validation, deployment, and rollback procedures Implement continuous training pipelines using MLFlow, Kubeflow, and Weights & Biases Design and maintain model monitoring systems for drift detection, performance degradation, and data quality issues Establish model governance frameworks ensuring reproducibility and auditability Data Validation & Quality Assurance Lead the development of pre-model and post-model validation frameworks using DeepChecks, Great Expectations, and custom validation rules Implement fairness and bias detection systems using Fairlearn and custom algorithmic auditing tools Design comprehensive data quality monitoring and alerting systems Conduct statistical testing and hypothesis validation for model performance claims Compliance & Security Ensure PII protection and DPDP compliance through secure data preprocessing and anonymization techniques Implement synthetic data generation pipelines using Gretel.ai and other privacy-preserving technologies Design policy-driven access controls and data governance frameworks using Apache Griffin and DataHub Conduct privacy impact assessments and implement differential privacy techniques where applicable Model Explainability & Auditing Develop comprehensive model explainability frameworks using SHAP, LIME, and custom interpretation tools Conduct reasoning-based walkthroughs and accuracy audits for deployed models Perform bias analysis and fairness assessments across different demographic groups Design and implement A/B testing frameworks for model performance evaluation Data Engineering & Pipeline Architecture Design and implement scalable ETL/ELT pipelines using Apache Spark, Flink, and modern data processing frameworks Leverage Redis for intelligent caching strategies and real-time feature serving Implement streaming data processing using Apache Kafka, RabbitMQ, and event-driven architectures Optimize data pipeline performance and ensure data consistency across distributed systems (ref:hirist.tech) Show more Show less

Job Title: Data Scientist Electric Load Forecasting Location: Mumbai / Pune Job Type: Full-time Experience: 3-5 years About the Role: We are seeking a highly motivated Data Scientist – Forecasting with a strong passion for energy, technology, and data-driven decision-making. In this role, you will be responsible for developing and refining energy load forecasting models , analyzing customer demand patterns , and improving forecasting accuracy using advanced time series analysis and machine learning techniques . Your insights will directly support risk management, operational planning, and strategic decision-making across the company. If you thrive in a fast-paced, dynamic environment and enjoy solving complex data science challenges , we’d love to hear from you! Key Responsibilities: Develop and enhance energy load forecasting models using time series forecasting , statistical modeling , and machine learning techniques . Analyze historical and real-time energy consumption data to identify trends and improve forecasting accuracy. Investigate discrepancies between forecasted and actual energy usage , providing actionable insights. Automate data pipelines and forecasting workflows to streamline processes across departments. Monitor day-over-day forecast variations and communicate key insights to stakeholders. Work closely with internal teams and external vendors to refine forecasting methodologies . Perform scenario analysis to assess seasonal patterns, anomalies, and market trends. Continuously optimize forecasting models , leveraging techniques like ARIMA, Prophet, LSTMs, and regression-based models . Qualifications & Skills: 3-5 years of experience in data science, preferably in energy load forecasting , demand prediction, or a related field. Strong expertise in time series analysis , forecasting algorithms , and statistical modeling . Proficiency in Python , with experience using libraries such as pandas, NumPy, scikit-learn, statsmodels, and TensorFlow/PyTorch . Experience working with SQL and handling large datasets. Hands-on experience with forecasting models like ARIMA, SARIMA, Prophet, LSTMs, XGBoost, and random forests . Familiarity with feature engineering, anomaly detection, and seasonality analysis . Strong analytical and problem-solving skills with a data-driven mindset . Excellent communication skills, with the ability to translate technical findings into business insights . Ability to work independently and collaboratively in a fast-paced, dynamic environment . Strong attention to detail, time management, and organizational skills. Preferred Qualifications (Nice to Have): Experience working with energy market data, smart meter analytics, or grid forecasting . Knowledge of cloud platforms (AWS) for deploying forecasting models . Experience with big data technologies such as Spark or Hadoop .