244 Arima Jobs - Page 10

Required Skills: Successful candidates will have demonstrated the following skills and characteristics: Must Have: Proven expertise in supply chain analytics across domains such as demand forecasting, inventory optimization, logistics, segmentation, and network design Well versed and hands-on experience of working on optimization methods like linear programming, mixed integer programming, scheduling optimization. Having understanding of working on third party optimization solvers like Gurobi will be an added advantage Proficiency in forecasting techniques (e.g., Holt-Winters, ARIMA, ARIMAX, SARIMA, SARIMAX, FBProphet, NBeats) and machine learning techniques (supervised and unsupervised) Strong command of statistical modeling, testing, and inference Proficient in using GCP tools: BigQuery, Vertex AI, Dataflow, Looker Building data pipelines and models for forecasting, optimization, and scenario planning Strong SQL and Python programming skills; experience deploying models in GCP environment Knowledge of orchestration tools like Cloud Composer (Airflow) Nice to have: Familiarity with MLOps, containerization (Docker, Kubernetes), and orchestration tools (e.g., Cloud composer) Strong communication and stakeholder engagement skills at the executive level Roles and Responsibilities: Assist analytics projects within the supply chain domain, driving design, development, and delivery of data science solutions Develop and execute on project & analysis plans under the guidance of Project Manager Interact with and advise consultants/clients in US as a subject matter expert to formalize data sources to be used, datasets to be acquired, data & use case clarifications that are needed to get a strong hold on data and the business problem to be solved Drive and Conduct analysis using advanced analytics tools and coach the junior team members Implement necessary quality control measures in place to ensure the deliverable integrity like data quality, model robustness, and explainability for deployments. Validate analysis outcomes, recommendations with all stakeholders including the client team Build storylines and make presentations to the client team and/or PwC project leadership team Contribute to the knowledge and firm building activities Role & responsibilities Preferred candidate profile

Job Description We are looking for an experienced Data Scientist with a specialization in forecasting to join our data science team. The ideal candidate will have a deep understanding of statistical and machine learning techniques for time series forecasting and demand prediction. In this role, you will drive business value by developing accurate forecasting models and delivering actionable insights to optimize decision-making processes across the organization . Key Responsibilitie s: Develop and implement advanced time series forecasting models to predict key business metrics (e.g., sales, demand, inventory, etc .).Analyze historical data to identify trends, seasonality, and other patterns that can be leveraged for accurate forecasti ng.Collaborate closely with client’s cross-functional teams such as Supply Chain, Finance, and Marketing to understand business needs and deliver tailored forecasting solutio ns.Build and optimize machine learning models for forecasting using state-of-the-art techniques (e.g., ARIMA, Prophet, LSTM, etc .).Design and run experiments to validate forecasting models and continuously improve their accuracy and reliabili ty.Communicate complex data-driven insights and forecasting results to both technical and non-technical stakeholde rs.Ensure high-quality data inputs for forecasting models by working with data engineering teams to improve data collection, transformation, and integration process es.Stay current with the latest advancements in forecasting methodologies, tools, and techniques, and apply them to enhance existing mode ls.Provide thought leadership in forecasting and predictive analytics, driving innovation within the data science te am.Mentor junior team members and help establish best practices for forecasting across the organizati on. Qualificat ions Master’s or Ph.D. in Data Science, Statistics, Economics, Applied Mathematics, or a related quantitative f ield.4+ years of experience in developing and deploying forecasting models in a business environ ment.Expertise in time series analysis and forecasting techniques, including ARIMA, SARIMA, Holt-Winters, and advanced machine learning methods like gradient boosting, neural networks (e.g., LSTM, GRU), etc.Proficiency in programming languages such as Python or R, with strong experience in data manipulation, model building, and statistical anal ysis.Hands-on experience with forecasting tools and libraries, such as Prophet, scikit-learn, TensorFlow, PyTorch, etc.Strong understanding of data structures, data wrangling, and working with large data sets.Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and working in a distributed data environment is a plus.Excellent problem-solving skills and ability to translate complex data into actionable insi ghts.Strong communication and presentation skills, with the ability to convey complex concepts to both technical and non-technical audie nces.Experience with visualization tools like Tableau, Power BI, or similar to present forecasting outc omes.Ability to work independently and collaboratively in a fast-paced environ ment. Preferred Qualifica tions:Experience with demand forecasting, sales forecasting, or supply chain optimization in industries such as retail, manufacturing, or fi nance.Familiarity with statistical testing and experimentation (e.g., A/B tes ting).Experience deploying models in production environments and collaborating with engineering teams to build scalable solu tions.Previous experience in a consulting or client-facing role is a plus. Show more Show less

Job Title: RCM Trainee Credentialing and Billing Operations Location: Gurugram, India Company: Neolytix Experience Required: Freshers (0–1 year) Employment Type: Full-time (Onsite role, 5-day work week) About Us Neolytix is a fast-growing healthcare services company looking to onboard fresh graduates as Management Trainees to build future-ready professionals in the field of Revenue Cycle Management (RCM) . This role is ideal for individuals who are looking to build a long-term career in medical billing, healthcare operations, and client delivery. You will be part of a structured, in-depth training and career progression journey where you’ll gain domain knowledge, hands-on experience, and the opportunity to grow into leadership roles. Why Join Neolytix? Get comprehensive training in US healthcare and RCM processes Gain hands-on exposure in a live business environment Work in a collaborative and fast-paced team Build your career with opportunities to specialize, lead, and mentor Enjoy a professional work culture with growth-driven mentorship Program Overview As a Management Trainee, your first three months will be a probationary period. This includes one week of onboarding followed by one month of service-specific training and continuous assessments. The training covers key areas such as the US healthcare system, insurance types, CPT coding, and RCM workflows. After training, you’ll begin working in a specific operational domain to apply your learning in real scenarios. Within 3 to 6 months, you will be groomed into a specialist in the RCM function. After one-year, top performers will have the opportunity to lead accounts, mentor new trainees, or manage small teams. Key Responsibilities Participate in structured training on RCM, medical billing, insurance, and healthcare workflows Assist operational teams in live projects and understand key performance metrics Apply theoretical concepts in assigned functional areas such as claims processing, payment posting, or denial management Support team leads in achieving client SLAs and compliance targets Continuously learn and adapt to changes in US healthcare rules and client requirements Progress into specialized or leadership roles based on performance and initiative Qualifications & Skills Recent graduates with a background in Science or Commerce with Math (preferred degrees: B.Sc, BCA, BBA, B.Com, or similar analytical/technical courses ) Minimum 65% aggregate in 12th grade (CBSE/ICSE or equivalent) Strong English communication and comprehension skills Basic proficiency in Microsoft Excel and Word Schooling from Delhi-NCR or other Tier-1/Cosmopolitan cities is preferred Strong analytical skills, willingness to learn, and high attention to detail Note: Applications not meeting the above eligibility criteria will not be considered. Salary Up to 3 LPA (based on performance and evaluation during training period) How to Apply If you're looking to start your career in healthcare operations, learn industry-leading skills, and grow with a forward-thinking team — Neolytix is the place for you. Apply now and start your journey in Revenue Cycle Management with us!

Flexing It is a freelance consulting marketplace that connects freelancers and independent consultants with organisations seeking independent talent. Flexing It has partnered with Our client, A leading global FMCG firm is seeking a detail-oriented and analytical Statistical Forecasting Analyst. The ideal candidate will be responsible for developing, maintaining, and improving statistical models to forecast demand, sales, or other key business metrics. This role requires strong analytical skills, proficiency in statistical software, and the ability to translate complex data into actionable insights that support strategic decision-making. Key responsibilities: ● Develop and maintain statistical models for short-term and long-term forecasting. ● Analyze historical data and identify trends, seasonality, and outliers to enhance forecast accuracy. ● Collaborate with cross-functional teams (e.g., sales, marketing, finance, supply chain) to understand forecasting requirements and business drivers. ● Perform scenario analysis and sensitivity testing to evaluate forecast robustness. ● Utilize software tools and programming languages (e.g., Python, R, SQL, Excel, SAS) for data manipulation and model development. ● Communicate forecasting results and insights through clear visualizations, dashboards, and presentations. ● Continuously refine forecasting processes and recommend improvements to enhance accuracy and efficiency. ● Monitor forecast performance using key metrics (e.g., MAPE, RMSE) and adjust models accordingly. ● Support demand planning or financial planning functions with accurate forecast inputs Skills required: ● Bachelor’s or Master’s degree in Statistics, Mathematics, Data Science, Economics, or a related quantitative field. ● 3+ years of experience in statistical modeling, forecasting, or related analytics roles. ● Strong knowledge of time series analysis and forecasting methodologies (e.g., ARIMA, exponential smoothing, regression, machine learning approaches). ● Proficiency in statistical and data analysis tools such as Python, R, SQL, Excel, or SAS. ● Experience with data visualization tools like Power BI, Tableau, or similar. ● Strong problem-solving, critical thinking, and communication skills. ● Ability to work independently and collaboratively in a fast-paced environment Show more Show less

About Hakkoda Hakkoda, an IBM Company, is a modern data consultancy that empowers data driven organizations to realize the full value of the Snowflake Data Cloud. We provide consulting and managed services in data architecture, data engineering, analytics and data science. We are renowned for bringing our clients deep expertise, being easy to work with, and being an amazing place to work! We are looking for curious and creative individuals who want to be part of a fast-paced, dynamic environment, where everyone’s input and efforts are valued. We hire outstanding individuals and give them the opportunity to thrive in a collaborative atmosphere that values learning, growth, and hard work. Our team is distributed across North America, Latin America, India and Europe. If you have the desire to be a part of an exciting, challenging, and rapidly-growing Snowflake consulting services company, and if you are passionate about making a difference in this world, we would love to talk to you!. We are seeking an exceptional and highly motivated Lead Data Scientist with a PhD in Data Science, Computer Science, Applied Mathematics, Statistics, or a closely related quantitative field, to spearhead the design, development, and deployment of an automotive OEM’s next-generation Intelligent Forecast Application. This pivotal role will leverage cutting-edge machine learning, deep learning, and statistical modeling techniques to build a robust, scalable, and accurate forecasting system crucial for strategic decision-decision-making across the automotive value chain, including demand planning, production scheduling, inventory optimization, predictive maintenance, and new product introduction. The successful candidate will be a recognized expert in advanced forecasting methodologies, possess a strong foundation in data engineering and MLOps principles, and demonstrate a proven ability to translate complex research into tangible, production-ready applications within a dynamic industrial environment. This role demands not only deep technical expertise but also a visionary approach to leveraging data and AI to drive significant business impact for a leading automotive OEM. Role Description Strategic Leadership & Application Design: Lead the end-to-end design and architecture of the Intelligent Forecast Application, defining its capabilities, modularity, and integration points with existing enterprise systems (e.g., ERP, SCM, CRM). Develop a strategic roadmap for forecasting capabilities, identifying opportunities for innovation and the adoption of emerging AI/ML techniques (e.g., generative AI for scenario planning, reinforcement learning for dynamic optimization). Translate complex business requirements and automotive industry challenges into well-defined data science problems and technical specifications. Advanced Model Development & Research: Design, develop, and validate highly accurate and robust forecasting models using a variety of advanced techniques, including: Time Series Analysis: ARIMA, SARIMA, Prophet, Exponential Smoothing, State-space models. Machine Learning: Gradient Boosting (XGBoost, LightGBM), Random Forests, Support Vector Machines. Deep Learning: LSTMs, GRUs, Transformers, and other neural network architectures for complex sequential data. Probabilistic Forecasting: Quantile regression, Bayesian methods to capture uncertainty. Hierarchical & Grouped Forecasting: Managing forecasts across multiple product hierarchies, regions, and dealerships. Incorporate diverse data sources, including historical sales, market trends, economic indicators, competitor data, internal operational data (e.g., production schedules, supply chain disruptions), external events, and unstructured data. Conduct extensive exploratory data analysis (EDA) to identify patterns, anomalies, and key features influencing automotive forecasts. Stay abreast of the latest academic researchand industry advancements in forecasting, machine learning, and AI, actively evaluating and advocating for their practical application within the OEM. Application Development & Deployment (MLOps): Architect and implement scalable data pipelines for ingestion, cleaning, transformation, and feature engineering of large, complex automotive datasets. Develop robust and efficient code for model training, inference, and deployment within a production environment. Implement MLOps best practices for model versioning, monitoring, retraining, and performance management to ensure the continuous accuracy and reliability of the forecasting application. Collaborate closely with Data Engineering, Software Development, and IT Operations teams to ensure seamless integration, deployment, and maintenance of the application. Performance Evaluation & Optimization: Define and implement rigorous evaluation metrics for forecasting accuracy (e.g., MAE, RMSE, MAPE, sMAPE, wMAPE, Pinball Loss) and business impact. Perform A/B testing and comparative analyses of different models and approaches to continuously improve forecasting performance. Identify and mitigate sources of bias and uncertainty in forecasting models. Collaboration & Mentorship: Work cross-functionally with various business units (e.g., Sales, Marketing, Supply Chain, Manufacturing, Finance, Product Development) to understand their forecasting needs and integrate solutions. Communicate complex technical concepts and model insights clearly and concisely to both technical and non-technical stakeholders. Provide technical leadership and mentorship to junior data scientists and engineers, fostering a culture of innovation and continuous learning. Potentially contribute to intellectual property (patents) and present findings at internal and external conferences. Qualifications Education: PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Experience: 5+ years of hands-on experience in a Data Scientist or Machine Learning Engineer role, with a significant focus on developing and deploying advanced forecasting solutions in a production environment. Demonstrated experience designing and developing intelligent applications, not just isolated models. Experience in the automotive industry or a similar complex manufacturing/supply chain environment is highly desirable. Technical Skills: Expert proficiency in Python (Numpy, Pandas, Scikit-learn, Statsmodels) and/or R. Strong proficiency in SQL. Machine Learning/Deep Learning Frameworks: Extensive experience with TensorFlow, PyTorch, Keras, or similar deep learning libraries. Forecasting Specific Libraries: Proficiency with forecasting libraries like Prophet, Statsmodels, or specialized time series packages. Data Warehousing & Big Data Technologies: Experience with distributed computing frameworks (e.g., Apache Spark, Hadoop) and data storage solutions (e.g., Snowflake, Databricks, S3, ADLS). Cloud Platforms: Hands-on experience with at least one major cloud provider (Azure, AWS, GCP) for data science and ML deployments. MLOps: Understanding and practical experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines). Data Visualization: Proficiency with tools like Tableau, Power BI, or similar for creating compelling data stories and dashboards. Analytical Prowess: Deep understanding of statistical inference, experimental design, causal inference, and the mathematical foundations of machine learning algorithms. Problem Solving: Proven ability to analyze complex, ambiguous problems, break them down into manageable components, and devise innovative solutions. Preferred Qualifications Publications in top-tier conferences or journals related to forecasting, time series analysis, or applied machine learning. Experience with real-time forecasting systems or streaming data analytics. Familiarity with specific automotive data types (e.g., telematics, vehicle sensor data, dealership data, market sentiment). Experience with distributed version control systems (e.g., Git). Knowledge of agile development methodologies. Soft Skills Exceptional Communication: Ability to articulate complex technical concepts and insights to a diverse audience, including senior management and non-technical stakeholders. Collaboration: Strong interpersonal skills and a proven ability to work effectively within cross-functional teams. Intellectual Curiosity & Proactiveness: A passion for continuous learning, staying ahead of industry trends, and proactively identifying opportunities for improvement. Strategic Thinking: Ability to see the big picture and align technical solutions with overall business objectives. Mentorship: Desire and ability to guide and develop less experienced team members. Resilience & Adaptability: Thrive in a fast-paced, evolving environment with complex challenges. Benefits Health Insurance Paid leave Technical training and certifications Robust learning and development opportunities Incentive Toastmasters Food Program Fitness Program Referral Bonus Program Hakkoda is committed to fostering diversity, equity, and inclusion within our teams. A diverse workforce enhances our ability to serve clients and enriches our culture. We encourage candidates of all races, genders, sexual orientations, abilities, and experiences to apply, creating a workplace where everyone can succeed and thrive. Ready to take your career to the next level? 🚀 💻 Apply today👇 and join a team that’s shaping the future!! Hakkoda is an IBM subsidiary which has been acquired by IBM and will be integrated in the IBM organization. Hakkoda will be the hiring entity. By Proceeding with this application, you understand that Hakkoda will share your personal information with other IBM subsidiaries involved in your recruitment process, wherever these are located. More information on how IBM protects your personal information, including the safeguards in case of cross-border data transfer, are available here. Show more Show less

Position : AI / ML Engineer Job Type : Full-Time Location : Gurgaon, Haryana, India Experience : 2 Years Industry : Information Technology Domain : Demand Forecasting in Retail/Manufacturing Job Summary We are seeking a skilled Time Series Forecasting Engineer to enhance existing Python microservices into a modular, scalable forecasting engine. The ideal candidate will have a strong statistical background, expertise in handling multi-seasonal and intermittent data, and a passion for model interpretability and real-time insights. Key Responsibilities Develop and integrate advanced time-series models: MSTL, Croston, TSB, Box-Cox. Implement rolling-origin cross-validation and hyperparameter tuning. Blend models such as ARIMA, Prophet, and XGBoost for improved accuracy. Generate SHAP-based driver insights and deliver them to a React dashboard via GraphQL. Monitor forecast performance with Prometheus and Grafana; trigger alerts based on degradation. Core Technical Skills Languages : Python (pandas, statsmodels, scikit-learn) Time Series : ARIMA, MSTL, Croston, Prophet, TSB Tools : Docker, REST API, GraphQL, Git-flow, Unit Testing Database : PostgreSQL Monitoring : Prometheus, Grafana Nice-to-Have : MLflow, ONNX, TensorFlow Probability Soft Skills Strong communication and collaboration skills Ability to explain statistical models in layman terms Proactive problem-solving attitude Comfort working cross-functionally in iterative development environments Job Type: Full-time Pay: ₹400,000.00 - ₹800,000.00 per year Application Question(s): Do you have at least 2 years of hands-on experience in Python-based time series forecasting? Have you worked in retail or manufacturing domains where demand forecasting was a core responsibility? Are you currently authorized to work in India without sponsorship? Have you implemented or used ARIMA, Prophet, or MSTL in any of your projects? Have you used Croston or TSB models for forecasting intermittent demand? Are you familiar with SHAP for model interpretability? Have you containerized a forecasting pipeline using Docker and exposed it through a REST or GraphQL API? Have you used Prometheus and Grafana to monitor model performance in production? Work Location: In person Application Deadline: 05/06/2025 Expected Start Date: 05/06/2025

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Manager- Data Science Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Our Team As consumer preference for digital payments continues to grow, ensuring a seamless and secure consumer experience is top of mind. Optimization Solutions team focuses on tracking of digital performance across all products and regions, understanding the factors influencing performance and the broader industry landscape. This includes delivering data-driven insights and business recommendations, engaging directly with key external stakeholders on implementing optimization solutions (new and existing), and partnering across the organization to drive alignment and ensure action is taken. Are you excited about Data Assets and the value they bring to an organization? Are you an evangelist for data-driven decision-making? Are you motivated to be part of a team that builds large-scale Analytical Capabilities supporting end users across 6 continents? Do you want to be the go-to resource for data science & analytics in the company? The Role Work closely with global optimization solutions team to architect, develop, and maintain advanced reporting and data visualization capabilities on large volumes of data to support data insights and analytical needs across products, markets, and services The candidate for this position will focus on Building solutions using Machine Learning and creating actionable insights to support product optimization and sales enablement. Prototype new algorithms, experiment, evaluate and deliver actionable insights. Drive the evolution of products with an impact focused on data science and engineering. Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models. Perform data ingestion, aggregation, and processing on high volume and high dimensionality data to drive and enable data unification and produce relevant insights. Continuously innovate and determine new approaches, tools, techniques & technologies to solve business problems and generate business insights & recommendations. Apply knowledge of metrics, measurements, and benchmarking to complex and demanding solutions. Role Ensure that all AI solutions follow industry standards for data management and privacy, covering aspects like data collection, use, storage, access, retention, output, reporting, and quality at Mastercard. Take a practical approach to AI, simplifying complex technical requirements to align with stakeholders' needs. Collaborate with global stakeholders to gather necessary information and define business problems. Think creatively to link AI methodologies with real business challenges. Identify common use case patterns to promote scalable AI through reusable models and a microservice approach. Build AI/ML solutions using the latest advancements from industry and academia. Use both open and proprietary technologies to address business problems. Work effectively across teams and geographies, leveraging broader team expertise to achieve AI goals. Partner with technical teams to deploy solutions in production environments. Foster a culture of learning and continuous improvement in AI capabilities. All About You 8+ years in Data Science, with a focus on AI strategy, execution, and solution development from the ground up. A passion for AI, demonstrated through participation in competitions such as Kaggle. Preferred experience or familiarity with cybersecurity, fraud, and risk solutions, including: Deep learning algorithms, open-source tools, and statistical environments (Python, R, SQL). Big data platforms like Hadoop, Hive, Spark, and GPU clusters for deep learning. Classical machine learning techniques such as Logistic Regression, Decision Trees, K-Means, PCA, and Time Series models (ARIMA/ARMA). Deep learning techniques including Random Forest, GBM, Neural Networks (CNNs, LSTMs), and optimization techniques (Adam, Adagrad, etc.). Frameworks like TensorFlow, Keras, PyTorch, and XGBoost for production systems. Experience or exposure to collaboration tools like Confluence, Bitbucket, ALM, etc. Knowledge of the payments industry and experience with SAFe (Scaled Agile Framework) is a plus. Effectiveness Ability to manage assumptions and validate them with key stakeholders under tight deadlines, while keeping development on track. Strong problem-solving skills, with the ability to break down complex issues and apply the right AI techniques to solve them. Deep attention to detail, ensuring high confidence in developed solutions. Strong understanding of technical system architecture and interdependencies, anticipating challenges and proactively solving them. Core Capabilities Excellent written and verbal communication skills. Strong project management experience. Background in Computer Science. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. R-245889 Show more Show less

Flexing It is a freelance consulting marketplace that connects freelancers and independent consultants with organisations seeking independent talent. Flexing It has partnered with Our client, A leading global FMCG firm is seeking a detail-oriented and analytical Statistical Forecasting Analyst. The ideal candidate will be responsible for developing, maintaining, and improving statistical models to forecast demand, sales, or other key business metrics. This role requires strong analytical skills, proficiency in statistical software, and the ability to translate complex data into actionable insights that support strategic decision-making. Key responsibilities: ● Develop and maintain statistical models for short-term and long-term forecasting. ● Analyze historical data and identify trends, seasonality, and outliers to enhance forecast accuracy. ● Collaborate with cross-functional teams (e.g., sales, marketing, finance, supply chain) to understand forecasting requirements and business drivers. ● Perform scenario analysis and sensitivity testing to evaluate forecast robustness. ● Utilize software tools and programming languages (e.g., Python, R, SQL, Excel, SAS) for data manipulation and model development. ● Communicate forecasting results and insights through clear visualizations, dashboards, and presentations. ● Continuously refine forecasting processes and recommend improvements to enhance accuracy and efficiency. ● Monitor forecast performance using key metrics (e.g., MAPE, RMSE) and adjust models accordingly. ● Support demand planning or financial planning functions with accurate forecast inputs Skills required: ● Bachelor’s or Master’s degree in Statistics, Mathematics, Data Science, Economics, or a related quantitative field. ● 3+ years of experience in statistical modeling, forecasting, or related analytics roles. ● Strong knowledge of time series analysis and forecasting methodologies (e.g., ARIMA, exponential smoothing, regression, machine learning approaches). ● Proficiency in statistical and data analysis tools such as Python, R, SQL, Excel, or SAS. ● Experience with data visualization tools like Power BI, Tableau, or similar. ● Strong problem-solving, critical thinking, and communication skills. ● Ability to work independently and collaboratively in a fast-paced environment Show more Show less

Company:- ABDOS Lamitubes Pvt. Ltd. (https://abdoslamitubes.com/) Position: - Safety Officer - EHS Experience: - 1 to 5+ Years Qualification: - Diploma/ B. Tech (Certificate Course of Industrial Safety from Govt. recognized) Salary:- Upto - 4.80 LPA Location:- Amingaon, Guwahati. Responsibilities: - Prepare and facilitate training on environment, health, and safety (EHS) measures imparted company. Should have experience on Hazardous waste management and statutory compliance of storage or Disposal of waste. Should have experience of consent management and hazardous disposal documentation. Should be aware about pollution control Board and liaisoning. EHS Documentation including SOPs, change controls, deviations, CAPA, validations, Data capturing etc. Expertise in GMP implementations, good practices in the organization, Environment Impact, and climate change Risk assessment & analysis, GHG emissions analysis, To organize safety committee meetings, drills and actively participate in the activities carried out regarding the safety in the concerned area. Significant solutions and implementing Environment, health safety management systems for maintaining sound environmental and safety conditions and development, repair, and modification of the plant. Role: - Planning and preparing EHS Calendar of all activities to be carried out during the year. Records related to EHS and MIS Compliance. Ensuring complete adherence to policies and sops related to EHS. EHS Awareness. Plant Development, Repairing and Modification. NOTE :- Manufacturing industry experience required only. Interested candidates can apply at neha.srivastava@abdoslmitubes.com or Whatsapp 8851314500 (Neha)

Company Description Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com Job Description We are looking for an experienced Data Scientist with a specialization in forecasting to join our data science team. The ideal candidate will have a deep understanding of statistical and machine learning techniques for time series forecasting and demand prediction. In this role, you will drive business value by developing accurate forecasting models and delivering actionable insights to optimize decision-making processes across the organization. Key Responsibilities Develop and implement advanced time series forecasting models to predict key business metrics (e.g., sales, demand, inventory, etc.). Analyze historical data to identify trends, seasonality, and other patterns that can be leveraged for accurate forecasting. Collaborate closely with client’s cross-functional teams such as Supply Chain, Finance, and Marketing to understand business needs and deliver tailored forecasting solutions. Build and optimize machine learning models for forecasting using state-of-the-art techniques (e.g., ARIMA, Prophet, LSTM, etc.). Design and run experiments to validate forecasting models and continuously improve their accuracy and reliability. Communicate complex data-driven insights and forecasting results to both technical and non-technical stakeholders. Ensure high-quality data inputs for forecasting models by working with data engineering teams to improve data collection, transformation, and integration processes. Stay current with the latest advancements in forecasting methodologies, tools, and techniques, and apply them to enhance existing models. Provide thought leadership in forecasting and predictive analytics, driving innovation within the data science team. Mentor junior team members and help establish best practices for forecasting across the organization. Qualifications Master’s or Ph.D. in Data Science, Statistics, Economics, Applied Mathematics, or a related quantitative field. 4+ years of experience in developing and deploying forecasting models in a business environment. Expertise in time series analysis and forecasting techniques, including ARIMA, SARIMA, Holt-Winters, and advanced machine learning methods like gradient boosting, neural networks (e.g., LSTM, GRU), etc. Proficiency in programming languages such as Python or R, with strong experience in data manipulation, model building, and statistical analysis. Hands-on experience with forecasting tools and libraries, such as Prophet, scikit-learn, TensorFlow, PyTorch, etc. Strong understanding of data structures, data wrangling, and working with large datasets. Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and working in a distributed data environment is a plus. Excellent problem-solving skills and ability to translate complex data into actionable insights. Strong communication and presentation skills, with the ability to convey complex concepts to both technical and non-technical audiences. Experience with visualization tools like Tableau, Power BI, or similar to present forecasting outcomes. Ability to work independently and collaboratively in a fast-paced environment. Preferred Qualifications Experience with demand forecasting, sales forecasting, or supply chain optimization in industries such as retail, manufacturing, or finance. Familiarity with statistical testing and experimentation (e.g., A/B testing). Experience deploying models in production environments and collaborating with engineering teams to build scalable solutions. Previous experience in a consulting or client-facing role is a plus. Additional Information Thrive & Grow with Us: Competitive Salary: Your skills and contributions are highly valued here, and we make sure your salary reflects that, rewarding you fairly for the knowledge and experience you bring to the table. Dynamic Career Growth: Our vibrant environment offers you the opportunity to grow rapidly, providing the right tools, mentorship, and experiences to fast-track your career. Idea Tanks: Innovation lives here. Our "Idea Tanks" are your playground to pitch, experiment, and collaborate on ideas that can shape the future. Growth Chats: Dive into our casual "Growth Chats" where you can learn from the best—whether it's over lunch or during a laid-back session with peers, it's the perfect space to grow your skills. Snack Zone: Stay fuelled and inspired! In our Snack Zone, you'll find a variety of snacks to keep your energy high and ideas flowing. Recognition & Rewards: We believe great work deserves to be recognized. Expect regular Hive-Fives, shoutouts and the chance to see your ideas come to life as part of our reward program. Fuel Your Growth Journey with Certifications: We’re all about your growth groove! Level up your skills with our support as we cover the cost of your certifications.

We're Hiring: Data Scientist Databricks & ML Deployment Expert Location: Mumbai Experience: 3-7 Years Apply Now! Are you passionate about deploying real-world machine learning solutions? We're looking for a versatile Data Scientist with deep expertise in Demand forecasting, Azure, Databricks, PySpark , Deployment , Classical ML and end-to-end ML deployment to drive impactful projects in the Retail and Automotive domains. What You will Do Develop scalable ML models (Regression, Classification, Clustering) Deliver advanced use cases like CLV modeling , Predictive Maintenance , and Time Series Forecasting Design and automate ML workflows on Databricks using PySpark Build and deploy APIs to serve ML models (Flask, FastAPI, Django) Own model deployment and monitoring in production environments Work closely with Data Engineering and DevOps teams for CI/CD integration Optimize pipelines and model performance (code & infrastructure level) Must-Have Skills Strong hands-on with Databricks and PySpark Proven track record in ML model development & deployment (min. 2 production deployments) Solid grasp of Regression, Classification, Clustering & Time Series Proficiency in SQL , workflow automation, and ELT/ETL processes API development (Flask, FastAPI, Django) CI/CD, deployment automation, and ML pipeline optimization Familiarity with Medallion Architecture Domain Expertise Retail: CLV, Pricing, Demand Forecasting Automotive : Predictive Maintenance, Time Series Nice to Have MLflow, Docker, Kubernetes Cloud: Azure, AWS, or GCP If you're excited to build production-ready ML systems that create real business impact, we want to hear from you! Apply Now to chaity.mukherjee@celebaltech.com or DM us for more info.

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.

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 .

Entity :- Accenture Strategy & Consulting Job location :- Mumbai About S&C - Global Network :- Accenture Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition WHATS IN IT FOR YOU Accenture CFO & EV team under Data & AI team has comprehensive suite of capabilities in Risk, Fraud, Financial crime, and Finance. Within risk realm, our focus revolves around the model development, model validation, and auditing of models. Additionally, our work extends to ongoing performance evaluation, vigilant monitoring, meticulous governance, and thorough documentation of models. Get to work with top financial clients globally Access resources enabling you to utilize cutting-edge technologies, fostering innovation with the worlds most recognizable companies. Accenture will continually invest in your learning and growth and will support you in expanding your knowledge. Youll be part of a diverse and vibrant team collaborating with talented individuals from various backgrounds and disciplines continually pushing the boundaries of business capabilities, fostering an environment of innovation. What you would do in this role Engagement Execution Work independently/with minimal supervision in client engagements that may involve model development, validation, governance, strategy, transformation, implementation and end-to-end delivery of risk solutions for Accentures clients. Ability to manage workstream of large projects / small projects with responsibilities of managing quality of deliverables for junior team members. Demonstrated ability of managing day to day interactions with the Client stakeholders Practice Enablement Guide junior team members. Support development of the Practice by driving innovations, initiatives. Develop thought capital and disseminate information around current and emerging trends in Risk. Qualification Who we are looking for 7 - 12 years of relevant Risk Analytics experience at one or more Financial Services firms, or Professional Services / Risk Advisory with significant exposure to one or more of the following areas: Development, validation, and audit of: Credit Risk- PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting and Revenue Forecasting Models, IFRS9/CECL Loss Forecasting Models across Retail and Commercial portfolios Credit Acquisition/Behavior/Collections/Recovery Modeling and Strategies, Credit Policies, Limit Management, Acquisition Frauds, Collections Agent Matching/Channel Allocations across Retail and Commercial portfolios Regulatory Capital and Economic Capital Models Liquidity Risk Liquidity models, stress testing models, Basel Liquidity reporting standards Anti Money Laundering AML scenarios/alerts, Network Analysis Operational risk AMA modeling, operational risk reporting Conceptual understanding of Basel/CCAR/DFAST/CECL/IFRS9 and other risk regulations Experience in conceptualizing and creating risk reporting and dashboarding solutions. Experience in modeling with statistical techniques such as linear regression, logistic regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time series ARMA/ARIMA, ML interpretability and bias algorithms etc. Programing Languages - SAS, R, Python, Spark, Scala etc., Tools such as Tableau, QlikView, PowerBI, SAS VA etc. Strong understanding of Risk function and ability to apply them in client discussions and project implementation. Academic : Masters degree in a quantitative discipline mathematics, statistics, economics, financial engineering, operations research or related field or MBA from top-tier universities. Strong academic credentials and publications, if applicable. Industry certifications such as FRM, PRM, CFA preferred. Excellent communication and interpersonal skills. Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.

About the Role We are seeking a Data Scientist with strong expertise in Python and SQL to join our growing data team. Youll work on data modeling, predictive analytics, and business intelligence projects that directly impact strategic decision-making. Key Responsibilities Extract, clean, and transform data from multiple sources using SQL and Python. Build predictive models and machine learning algorithms for business use cases. Perform exploratory data analysis (EDA) and generate actionable insights. Create interactive dashboards & reports (Power BI/Tableau). Optimize and maintain data pipelines, ETL processes, and workflows . Collaborate with cross-functional teams to translate business needs into analytical solutions. Present analytical results in a clear, visual, and business-friendly format. Required Skills 1–5 years of experience in Data Science or Data Analytics roles. Strong proficiency in Python (NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn). Advanced SQL skills (complex queries, joins, window functions, optimization). Understanding of machine learning algorithms and statistical methods. Experience in data visualization tools (Power BI, Tableau, or similar). Strong problem-solving and analytical skills. Bachelor’s/Master’s in Computer Science, Data Science, Statistics, Mathematics, or related fields. Nice to Have Familiarity with cloud platforms (AWS, Azure, GCP). Exposure to Big Data tools (Spark, Hadoop). Basic understanding of APIs and automation scripts . What We Offer Competitive industry-standard salary + performance incentives. Flexible working hours & hybrid/remote opportunities. Exposure to real-world, high-impact projects .

About Us Valiance is a global AI & Data analytics firm helping clients build cutting-edge technology solutions for digital transformation. We work with some of the marquee brands across India, US and APAC to build transformative solutions for Credit Risk, Fraud, Predictive Maintenance, Quality Inspection, Data lake, IOT analytics etc. Our team comprises 140+ professionals across Machine Learning, Data Engineering & Cloud expertise. Job Summary/Objective: The Data Scientist will be responsible for applying our pre-trained demand forecasting models to generate actionable insights and highly accurate forecasting outcomes. This role involves thorough data analysis, identifying trends and anomalies, interpreting results, and communicating findings effectively to a non-technical business audience. The ideal candidate is less focused on creating algorithms and more oriented towards solving business challenges and providing insights that make a tangible impact. Key Responsibilities: Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and anomalies in demand/Timeseries forecasting for Retail Industry very specific to Apparel and Footwear (must have) Model Utilization: Leverage existing pre-trained forecasting models, optimizing their performance by incorporating a nuanced understanding of data points and improving model outcomes based on data insights. Interpretation & Communication: Interpret model results and explain outcomes in simple, actionable terms for business stakeholders, ensuring clarity and relevance. Insights Generation: Develop insights that guide business decisions, aiming for highly accurate forecasting outcomes to meet business requirements. Collaboration: Work closely with cross-functional teams, including business stakeholders and analysts, to ensure forecasting outputs align with business objectives and provide real-world value. Continuous Improvement: Identify opportunities to improve model performance through better data usage and fine-tuning, rather than new model development. Required Skills & Qualifications: Experience: 3-8 years of experience in data science or a related field, specifically in Demand/Timeseries forecasting for Retail Industry very specific to Apparel and Footwear (must have) Technical Proficiency: Strong skills in data analysis, data visualization, and working with pre-trained ML models. Proficiency in Python, and SQL is preferred. Business Focus: Strong orientation towards solving business problems rather than a pure focus on machine learning algorithms. Communication Skills: Ability to clearly communicate insights and forecast results to non-technical stakeholders in simple, understandable language. Problem Solving: Demonstrated ability to interpret data, uncover actionable insights, and suggest practical solutions for business needs. Detail-Oriented: Thorough attention to detail, ensuring accuracy in forecasting and relevance of insights. Educational Background: Bachelors or Masters degree in Data Science, Statistics, Computer Science, or a related field.

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 Title: Data Scientist Time Series & Forecasting (Immediate Joiner) Employment Type: Permanent (Open to Contractors) Start Date: Immediate Hybrid Work Key Responsibilities: Develop and implement time series forecasting models for business-critical use cases. Leverage Databricks for data processing, transformation, and model deployment. Work with FMCG domain data to derive actionable insights and improve forecasting accuracy. Write clean, efficient, and production-ready Python code for data pipelines and ML models. Collaborate with business stakeholders and cross-functional teams to deliver analytical solutions. Must-Have Skills: Proven experience in time series analysis and forecasting techniques (ARIMA, Prophet, LSTM, etc.). Hands-on experience with Databricks. Strong expertise in Python coding for data science and analytics. FMCG industry experience. Ability to join immediately. Nice-to-Have: Experience with cloud platforms (Azure/AWS/GCP). Familiarity with advanced ML techniques and MLOps best practices.

About OJ Commerce: OJ Commerce (OJC), a rapidly expanding and profitable online retailer, is headquartered in Florida, USA, with a fully-functional office in Chennai, India. We deliver exceptional value to our customers by harnessing cutting-edge technology, fostering innovation, and establishing strategic brand partnerships to enable a seamless, enjoyable shopping experience featuring high-quality products at unbeatable prices. Our advanced, data-driven system streamlines operations with minimal human intervention. Our extensive product portfolio encompasses over a million SKUs and more than 2,500 brands across eight primary categories. With a robust presence on major platforms such as Amazon, Walmart, Wayfair, Home Depot, and eBay, we directly serve consumers in the United States. As we continue to forge new partner relationships, our flagship website, www.ojcommerce.com, has rapidly emerged as a top-performing e-commerce channel, catering to millions of customers annually. Responsibilities: • Develop, validate, and implement advanced statistical models, including mixed effects models, structural equation modelling, generalized additive models (GAMs), Bayesian modelling, and hierarchical models to address complex business challenges. • Analyze large datasets using statistical techniques to extract actionable insights and trends. • Collaborate with stakeholders to understand business needs and translate them into analytical solutions. • Present findings and recommendations clearly to both technical and non-technical audiences. • Stay current with industry trends, statistical methodologies, and best practices in data analysis. • Document methodologies and results, ensuring transparency and reproducibility of models. • Conduct exploratory data analysis to inform model development and improve accuracy. • Participate in continuous improvement initiatives to enhance modelling processes and tools. Qualifications: • Masters degree or above in Statistical Sciences. • Proven experience in statistical modeling, data analysis, and predictive analytics. • Very strong proficiency in statistical software (e.g., R, Python, SAS, SPSS) and data visualization tools (e.g., Tableau, Power BI). • Strong understanding of advanced statistical techniques, including regression analysis, time series forecasting, mixed effects models, structural equation modeling, generalized linear models (GLMs), machine learning algorithms (e.g., decision trees, random forests, support vector machines), and Bayesian inference. • Excellent problem-solving skills and attention to detail. • Strong communication skills, with the ability to convey complex statistical concepts to diverse audiences. • Experience with data management and database systems (e.g., SQL) is a plus. What we Offer • Competitive salary • Medical Benefits/Accident Cover • Flexi Office Working Hours • Fast paced start up