7 Sarima Jobs

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 .

As a Visiting Faculty for Time Series & Forecasting at our Mumbai campus, you will be responsible for delivering high-quality instruction to students enrolled in the B.Sc./M.Sc. program in Data Science & Business Analytics. Your role will involve imparting knowledge on various aspects of time series analysis, including ARIMA, SARIMA, decomposition, smoothing techniques, and the application of tools like Python (statsmodels), R, and Excel in real-world scenarios such as finance, operations, and sales prediction. To excel in this position, you should hold a postgraduate degree in Data Science, Statistics, or a related field, coupled with practical experience either in the industry or as a teacher specializing in Time Series & Forecasting. Proficiency in statistical modeling using Python/R is essential, as well as the ability to effectively engage and educate both undergraduate and postgraduate students. Your teaching approach should be classroom-oriented with a focus on practical case studies to enhance learning outcomes. Please note that this role is specifically based in Mumbai and requires delivering lectures on weekdays. Candidates residing outside Mumbai will not be considered for this position. If you meet the requirements and are passionate about educating the next generation of data science professionals, we encourage you to apply by sending your CV to info@sdbi.in with the subject line "Application Visiting Faculty (Time Series) Mumbai".,

As an experienced Data Scientist with expertise in Machine Learning and NLP/GenAI, you will have the exciting opportunity to join our dynamic team and work on challenging data science projects that have a significant impact on our client outcomes. Your key responsibilities will include leading and growing client accounts with onshore stakeholders, managing the accounts delivery team focused on data science and AI, preparing responses for Request for Proposal and Request for Information, developing quick Proof of concepts for client visits and demos, implementing advanced machine learning models and GenAI based solutions in client projects, and ensuring solid understanding of NLP from transformers to the new generation LLMs. In addition, you will be required to develop and maintain documentation for models, processes, and code to ensure reproducibility and knowledge sharing, as well as effectively communicate results and insights to both technical and non-technical stakeholders. For qualifications, you should hold a Bachelors or Masters degree in computer science, Statistics, Mathematics, Data Science, Economics or a related field. You should possess strong skills in Python, SQL, API and backend integration, code version control, in-depth knowledge of machine learning algorithms and statistical methods used in client engagements, and hands-on experience with Retriever Augmented Generations and Agentic Frameworks. Moreover, you should have hands-on experience with time series forecasting models such as ARIMA, SARIMA, Exponential Smoothing, Prophet, LSTM, and others, code version control, docker-based model deployment knowledge, and familiarity with at least one cloud provider among Azure, GCP, or AWS. Your ability to manage multiple projects and meet tight deadlines in a fast-paced environment, willingness to adapt to new technologies, strong analytical and problem-solving skills, attention to detail, and excellent communication skills will be crucial for success in this role. With 14-20 years of experience, you are well-positioned to excel in this challenging and rewarding opportunity.,

At PwC, the focus in data and analytics is on leveraging data to drive insights and make informed business decisions. Utilizing advanced analytics techniques to help clients optimize their operations and achieve strategic goals is key. In data analysis at PwC, the emphasis is on utilizing advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. Skills in data manipulation, visualization, and statistical modeling play a crucial role in supporting clients in solving complex business problems. Candidates with 4+ years of hands-on experience are sought for the position of Senior Associate in supply chain analytics. Successful candidates should possess proven expertise in supply chain analytics across domains such as demand forecasting, inventory optimization, logistics, segmentation, and network design. Additionally, hands-on experience working on optimization methods like linear programming, mixed integer programming, and scheduling optimization is required. Proficiency in forecasting techniques and machine learning techniques, along with a strong command of statistical modeling, testing, and inference, is essential. Familiarity with GCP tools like BigQuery, Vertex AI, Dataflow, and Looker is also necessary. Required skills include building data pipelines and models for forecasting, optimization, and scenario planning, strong SQL and Python programming skills, experience deploying models in a GCP environment, and knowledge of orchestration tools like Cloud Composer (Airflow). Nice-to-have skills consist of familiarity with MLOps, containerization (Docker, Kubernetes), and orchestration tools, as well as strong communication and stakeholder engagement skills at the executive level. The roles and responsibilities of the Senior Associate involve assisting analytics projects within the supply chain domain, driving design, development, and delivery of data science solutions. They are expected to interact with and advise consultants/clients as subject matter experts, conduct analysis using advanced analytics tools, and implement quality control measures for deliverable integrity. Validating analysis outcomes, making presentations, and contributing to knowledge and firm building activities are also part of the role. The ideal candidate should hold a degree in BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA from a reputed institute.,

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 .

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 .

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.