331 Predictive Analytics jobs in Hyderabad

Optiply is at the forefront of three rapidly expanding sectors: Software as a Service, Artificial Intelligence, and E-commerce. With our intelligent purchasing software, we empower over 300 web shops and wholesalers to make smarter buying decisions, using predictive analytics to optimize inventory management. We're not just building a product;
we're building the future of autonomous inventory management.

At Optiply, we run millions of demand forecasts every day to optimize the global e-commerce supply chain. As our Time Series Forecasting Engineer, you won't just be building models;
you'll be engineering the core intelligence of a system that operates at a massive scale. You will be responsible for the performance, accuracy, and scalability of the algorithms that form the backbone of our product. This is a unique opportunity to make a significant impact in a high-volume, production environment, working across both Python and R to solve complex forecasting challenges.

• Architect, enhance, and maintain our forecasting systems, working across both our Python and R codebases to deliver robust, scalable solutions.
• Take ownership of improving the accuracy and performance of models that are already running on millions of time series daily.
• Research, prototype, and implement next-generation forecasting algorithms (from statistical methods to ML/deep learning) capable of performing on large-scale datasets.
• Enhance and refactor our existing forecasting models in R while leading the development of new
• Develop and own the MLOps pipelines for our forecasting models, including automated training, deployment, A/B testing, and monitoring for performance at scale.
• Collaborate with Backend Engineers and Data Scientists to ensure our forecasting engine is seamlessly and efficiently integrated into our product.

• You have 3–6 years of professional experience building and deploying machine learning models in a high-volume production environment, with a strong focus on time series forecasting.
• Proven expertise in both Python and/or R for production-level data science. You are an expert in at least one, with professional, hands-on experience in the other.
• Python: pandas, scikit-learn, LightGBM/XGBoost, etc.
• R: dplyr, data.Table, forecast/fable, tidymodels, etc.
• Demonstrated experience working with large-scale data and building high-performance, production-grade ML systems.
• Deep theoretical and practical understanding of time series analysis, from classical statistical models (ARIMA, ETS) to modern machine learning techniques.
• Hands-on experience with software engineering best practices and tools, including Git, Docker, and CI/CD pipelines.
• Strong experience with SQL for complex data extraction and analysis.
• You are a pragmatic problem-solver, driven by the challenge of optimizing a complex system and delivering measurable business impact.

• Experience with probabilistic forecasting and inventory optimization techniques.
• Exposure to cloud platforms (GCP, AWS, or Azure) and MLOps tools (e.G., MLflow, Kubeflow).
• Experience with large-scale data processing tools (e.G., Spark, Dask).
• Prior experience in a SaaS, e-commerce, or supply chain tech company.

• Competitive Compensation Package: Reflects your skills and contributions.
• Holistic Work-Life Harmony: We value your personal time and promote a healthy work-life balance.
• Comprehensive Health Coverage: Robust insurance plans for your peace of mind.
• Investment in Professional Growth: We invest in your development with paid training programs.
• Adaptable Work Hours: We offer flexibility in your work schedule.
• Hybrid Work Model: Enjoy a blend of remote and in-office work.
• Strategic Career Development: We provide personalized growth plans and advancement opportunities.
• Tailored Workspace Setup: Get a high-quality PC, monitor, keyboard, and other essentials.
• Social Fridays: Wind down the week with casual drinks and foster team camaraderie.

• Then send us your CV in English and get prepared to meet our team! We are excited to see how you can help us scale the future of inventory optimization.

Job Role

The Solution Consultant's primary responsibility is to participate in implementations of Predictive Analytics portfolio. This role will involve working under the direction of a Project Manager and Technical Lead to ensure customer satisfaction and an on-time / on-budget delivery.

Key responsibilities

- Supports qualified business capture activities to include site visits, demonstrations, proof of concepts.

- Undertakes data preparation tasks under the guidance of the Project SME and/or technical lead.

- Contributes to technical project deliverables, taking responsibility of accuracy and flow of content.

- Operates independently based on high level work descriptions. Prioritizes activities based on impact to the project.

- Predicts obstacles in advance and works to prevent them by altering plans or creating new solutions.

- Employs fault diagnosis techniques to assess issues and provide solutions or workarounds.

- Manages own time effectively within the scope of work allocated and ensures timely delivery.

Essential requirements

• Masters or BS degree in Mechanical/Chemical Engineering or the equivalent.

Desired skills

• Good understanding of solving complex problems, ability to read PnID Diagrams will give advantage.
• Significant Experience providing engineering expertise in the application, operation, inspection and maintenance of plant systems and rotating equipment normally associated with oil & gas facilities and optimizing performance of Chemicals, Oil & Gas facilities (upstream, mid-stream, and/or downstream)
• Experience with preventative and predictive maintenance practices (including software packages such as PRiSM or Smart Signal or its equivalent) for major rotating and static equipment such as compressors and pumps with large prime movers (- gas turbines, steam turbines & motors), Blowers, fans, fired heaters, distillation columns, Transformers, Heat exchangers (including cryogenics) etc.
• Has experience of some elements of the complete project lifecycle for delivery of projects to include scoping, requirements gathering, design, build, test, training, and roll-out.
• Responsible to deliver the models for rotating and static assets for various industries like O&G, Power, cement, Electrical distribution etc.,
• Experienced in FAT, SAT, pre-commissioning, commissioning, operation, support, and trouble shooting.
• Has good working knowledge of the Oil & Gas Industry, Power to include EPCs and Owner Operators is preferred.
• Added advantage in several of the following: C#, .NET framework, JavaScript, XML, PowerShell, SQL, SSRS/SSIS, MS Office tools.
• Flexible to travel within the region and potentially more widely to perform project delivery and consultancy tasks to support business goals.
• Possesses excellent written and spoken English skills
• Demonstrates sound presentation skills.

• Lead the design, development, and deployment of predictive models and machine learning solutions to address complex business challenges.
• Mentor and guide a team of data scientists, fostering a culture of innovation and technical excellence.
• Collaborate with stakeholders across various industries to understand business requirements and translate them into data science problems.
• Develop and implement robust data analysis frameworks, ensuring data integrity and validity.
• Perform in-depth exploratory data analysis to identify trends, patterns, and anomalies.
• Select appropriate statistical techniques and machine learning algorithms for predictive modeling, classification, regression, and clustering.
• Build, train, and evaluate machine learning models, optimizing for performance and accuracy.
• Develop and maintain scalable data pipelines and infrastructure for model deployment and monitoring.
• Communicate complex analytical findings and recommendations clearly and concisely to business leaders through compelling visualizations and presentations.
• Stay current with the latest advancements in data science, machine learning, and artificial intelligence.
• Identify opportunities for leveraging new data sources and advanced analytical techniques.
• Ensure the ethical and responsible use of data and AI technologies.
• Contribute to the strategic vision for data science within the organization.
• Manage project timelines, resources, and deliverables effectively.
• Troubleshoot and resolve issues related to data, models, and deployment pipelines.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
• 7+ years of experience in data science or a related analytical role, with a proven track record of leading projects and teams.
• Expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and model evaluation techniques.
• Proficiency in programming languages such as Python or R, and experience with data science libraries (e.g., scikit-learn, pandas, NumPy, TensorFlow, PyTorch).
• Strong SQL skills and experience with database management.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent understanding of data visualization tools (e.g., Tableau, Power BI, Matplotlib).
• Strong analytical, problem-solving, and critical thinking skills.
• Exceptional communication and presentation skills, with the ability to explain technical concepts to non-technical audiences.
• Demonstrated ability to work independently and collaboratively in a remote environment.
• Experience in managing cloud-based data science platforms (e.g., AWS SageMaker, Azure ML, GCP AI Platform) is desirable.
• Strong leadership and team management capabilities.

• Lead the end-to-end development of machine learning models, from data preprocessing and feature engineering to model training, evaluation, and deployment.
• Design and implement scalable AI/ML systems and pipelines.
• Stay abreast of the latest research and advancements in AI, ML, deep learning, and related fields.
• Mentor and guide junior AI/ML engineers and data scientists.
• Collaborate with cross-functional teams to understand business needs and identify areas where AI/ML can provide value.
• Develop robust MLOps practices for model monitoring, retraining, and version control.
• Evaluate and select appropriate algorithms and tools for specific predictive modeling tasks.
• Present complex findings and technical solutions to both technical and non-technical audiences.
• Contribute to the technical strategy and roadmap for AI/ML initiatives.
• Ensure the ethical and responsible use of AI/ML technologies.

• Master's or Ph.D. in Computer Science, Data Science, Statistics, or a related quantitative field.
• 7+ years of hands-on experience in developing and deploying machine learning models.
• Proven experience in leading AI/ML projects and teams.
• Expertise in Python and associated libraries (e.g., TensorFlow, PyTorch, scikit-learn, Pandas, NumPy).
• Strong understanding of statistical modeling, algorithms, and data mining techniques.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
• Excellent problem-solving, analytical, and communication skills.
• Ability to work independently and as part of a collaborative team.

Job Description:

Role: Data Analyst- Sr. Associate

Experience: 5-12 Years

Skills: Data Analysis, DatawareHousing, Strong Sql, Python

Insurance Domain experience of minimum 3-4 years (Mandatory- reinsurance, actuaries. Good to have- annuities, liabilities)

• 7-9 years of experience as a Data Analyst, with at least 5 years supporting Finance within the insurance industry.
• Hands-on experience with Vertica/Teradata for querying, performance optimization, and large- scale data analysis.
• Advanced SQL skills: proficiency in Python is a strong plus.
• Proven ability to write detailed source-to-target mapping documents and collaborate with technical teams on data integration.
• Experience working in hybrid onshore-offshore team environments.
• Knowledge of data engineering principles: ETL/ELT, data lakes, and data warehousing.
• Deep understanding of data modeling concepts and experience working with relational and dimensional models.
• Strong communication skills with the ability to clearly explain technical concepts to non-technical audiences.
• A strong understanding of statistical concepts, probability and accounting standards, financial statements (balance sheet, income statement, cash flow statement), and financial ratios.
• Strong understanding of life insurance products and business processes across the policy lifecycle.
• Investment Principles: Knowledge of different asset classes, investment strategies, and financial markets.

Please share your resume to

• Analyze geological data from various sources, including remote sensing, seismic, and well logs.
• Develop and interpret geological models to identify potential mineral and hydrocarbon resources.
• Utilize GIS and geological software for data visualization, mapping, and analysis.
• Assess geological hazards and risks for exploration and development projects.
• Collaborate with exploration teams to plan field operations and data acquisition strategies.
• Prepare detailed technical reports and present findings to management and stakeholders.
• Stay abreast of advancements in geological technologies and methodologies.
• Contribute to the strategic planning and prioritization of exploration targets.
• Ensure data integrity and compliance with industry standards.
• Mentor junior geologists in data analysis techniques.

• Master's or Ph.D. in Geology, Earth Science, or a related field.
• Minimum of 7 years of experience in geological data analysis, preferably within the mining or exploration industry.
• Expertise in geological modeling software (e.g., Leapfrog, Petrel), GIS (e.g., ArcGIS, QGIS), and data analysis tools (e.g., Python, R).
• Strong understanding of remote sensing principles and interpretation of satellite imagery.
• Proven ability to interpret complex geological datasets and derive actionable insights.
• Excellent written and verbal communication skills.
• Demonstrated ability to work independently and manage projects effectively in a remote setting.
• Strong analytical and critical thinking skills.