206 Time Series Jobs - Page 3

Develop and implement sales forecasting models using advanced time series forecasting algorithms. Analyze and optimize pricing strategies to maximize revenue and profitability. Proven experience with time series forecasting techniques (ARIMA, Prophet, LSTM, etc.). Pandas, NumPy, Scikit-learn Proven experience with time series forecasting techniques (ARIMA, Prophet, LSTM, etc.). Expertise in sales forecasting and pricing strategy in a retail context. Location : - Remote,New Delhi,Mumbai,Bengaluru

Job overview: In this role, youll be part of our Data Science team. With a track record of innovation and taking large ML-based products from conception to delivering value, you will be responsible for developing ML and deep learning models to improve innovation within our Knowledge Graph curation. Your success will result in informed decision-making and stakeholder empowerment for Knowledge Graph use cases within Crayon. You will also directly impact the evolution of our content catalogue. Can you say Yes, I have! to the following? 5+ years of experience with developing solutionsusing machine learning, operation research and pattern searching methods onlarge scale data. B.E/B.Tech/MSin Machine Learning, Computer Science,Applied Statistics, Mathematics, or related fields. PhD is a plus Good understanding of statistical models likehierarchical models, stochastic models, time series, survival and econometricmodels Expert in at least one of the deep learningframeworks such as PyTorch, MxNet, or Tensorflow Hands-on experience in using Spark (Scalaor Pyspark) to process data at large scale and database schemadesign for ML pipelines a must Contribution to open-source ML packages/researchpublications will be a huge bonus Can yousay Yes, I will! to the following? 5+ years of experience with developing solutionsusing machine learning, operation research and pattern searching methods on largescale data. Good understanding on statistical models likehierarchical models, stochastic models, time series, survival and econometricmodels Expert in at least one of the deep learningframeworks such as PyTorch, MxNet, Tensorflow. Hands-on experience in using Spark (Scalaor Pyspark) to process data at large scale and database schemadesign for ML pipelines a must Contribution to open-source ML packages/researchpublications will be a huge bonus

About Firstsource Firstsource Solutions Limited, an RP-Sanjiv Goenka Group company (NSE: FSL, BSE: 532809, Reuters: FISO.BO, Bloomberg: FSOL:IN), is a specialized global business process services partner, providing transformational solutions and services spanning the customer lifecycle across Healthcare, Banking and Financial Services, Communications, Media and Technology, Retail, and other diverse industries. With an established presence in the US, the UK, India, Mexico, Australia, South Africa, and the Philippines, we make it happen for our clients, solving their biggest challenges with hyper-focused, domain-centered teams and cutting-edge tech, data, and analytics. Our real-world practitioners work collaboratively to deliver future-focused outcomes. Job Title: Senior Consultant Job Summary: As a Machine Learning Engineer specializing in generative AI, you will be responsible for designing, developing, and deploying advanced machine learning models that generate high-quality, human-like content. You will collaborate with cross-functional teams to integrate these models into our products, enhancing their capabilities and delivering exceptional value to our clients. Key Responsibilities: Develop, train, and optimize generative AI models for various applications, including text, image, and audio generation. Collaborate with product managers, software engineers, and data scientists to understand project requirements and deliver robust AI solutions. Conduct research to stay updated on the latest advancements in generative AI and apply best practices to improve model performance. Implement and maintain scalable machine learning pipelines for training and deploying models in production environments. Evaluate and fine-tune models to ensure they meet performance, accuracy, and efficiency standards. Perform data preprocessing, augmentation, and annotation to prepare high-quality datasets for model training. Troubleshoot and resolve issues related to model performance, data quality, and integration with other systems. Document model architecture, training processes, and performance metrics for internal and client-facing reports. Qualifications: Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Proven experience in developing and deploying generative AI models using frameworks such as TensorFlow, PyTorch, or similar. Strong programming skills in Python and proficiency with machine learning libraries and tools. Familiarity with natural language processing (NLP), computer vision, and other relevant AI techniques. Experience with cloud platforms such as AWS, Google Cloud, or Azure for model deployment and management. Knowledge of data preprocessing, feature engineering, and model evaluation techniques. Excellent problem-solving skills and the ability to work independently and as part of a team. Strong communication skills to effectively convey technical concepts to non-technical stakeholders. Preferred Qualifications: Experience with GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and other advanced generative models. Understanding of ethical considerations and bias mitigation in AI systems. Contributions to open-source projects or publications in relevant conferences/journals. Experience with MLOps practices and tools for continuous integration and deployment of machine learning models. Disclaimer: Firstsource follows a fair, transparent, and merit-based hiring process. We never ask for money at any stage. Beware of fraudulent offers and always verify through our official channels or @firstsource.com email addresses.

Position Purpose ODIN is a Data Warehouse application and it is changing its overall architecture and migrating to new efficient data model, Also few of the technical upgrade are due in this year. We are looking for the mid experience team member in the team, who can learn the BAU quickly and come up with fresh ideas in the team and contribute in designing and development of the statistical models. The team is in charge of the maintenance and the development of new features on 3 reporting applications as well as a Data Warehouse. These applications are designed to provide KPI and reports for back-office and valuation and risk control teams. Responsibilities Direct Responsibilities o Understand the need of Business/Operations teams, and propose indicators to meet the expectations. o Work on Big data environment. o Propose, when relevant, the architecture & flow of new applications that would help them integrate with existing ones and with the whole data architecture being developed o Develop, when relevant, different components of this architecture/flow of the applications. o Collect data from multiple various sources in ELK stack to calculate the new indicators. The indicators could be results from time series prediction, clustering, or other supervised or unsupervised machine learning algorithms o Automation of recurring actions and implementation of tools to facilitate the support and evolution of applications o Contribution to the evolution of the application architecture to improve the quality of service provided to users (Operations, Business) Contributing Responsibilities o Support and maintenance in operational condition of various applications focused on the collection and analysis of technical and functional data The technical environment consists of OS such as Windows, Linux Red Hat / Ubuntu, various technologies (Kafka, PostgreSQL, Hadoop, ELK, Qlik, API) and a DevOps part using Docker, Ansible, Kubernetes, Git, Jenkins and all of the Atlassian tools. Creation of processes to onboard new projects (Infrastructure and Business) Study and advice on the technological choice for evolutions and new projects Implementation and monitoring of action plans to avoid the recurrence of problems Technical and functional data analysis (Data Intelligence, Machine Learning, ) Technical & Behavioral Competencies Mandatory Technical expertise required: Oracle (+++) / T-SQL & PLSQL (+++) (preferably) - including optimization of stored procedures, queries, partitioning, local and global indexes, etc. Nice to have Technical skills: DWH Python Reporting tools and ETL ELK Stack Kibana ML Libraries Git and all of the Atlassian tools. Statistical/Machine Learning Modelling. Behavioral Skills Curiosity and analysis skills and willingness to learn. Good Communication skills. Quality-focused with a good eye for detail. Capacity to work in a high-pressure environment. Must be able to work closely with distributed team, users and business analysts. Willing to share knowledge and skills with other developers within the team. Whilst able to work independently, should be a true team player. Creativity and Problem solving attitude. Specific Qualifications (if required) Skills Referential Behavioural Skills : (Please select up to 4 skills) Decision Making Organizational skills Critical thinking Communication skills - oral & written Transversal Skills: (Please select up to 5 skills) Ability to understand, explain and support change Ability to develop and adapt a process Ability to develop others & improve their skills Analytical Ability Ability to inspire others & generate people's commitment Education Level: Bachelor Degree or equivalent

We are seeking a highly skilled and motivated Lead Data Scientist to join our team. In this role, you will leverage cutting-edge AI and machine learning technologies to solve complex business problems, design innovative data science solutions, and deliver projects that exceed client expectations. As a leader, you will manage a team of data scientists, collaborate with cross-functional data teams, and provide strategic and technical direction in data science while driving innovation in our product and solution offerings. Mandatory Technical Skills: • Strong statistical and machine learning intuition to address new and unique challenges. • Ability to design, develop and deploy end-to-end data science solutions, POCs and production-grade applications. • Strong proficiency in Python with OOP principles - ( 4 years of experience) • Experience developing APIs using Flask or Fast API frameworks – ( 2 years of experience) • Integration knowledge with front-end applications – ( 1 year of experience) • Expertise in version control systems (e.g., GitHub, GitLab, Azure DevOps) - ( 3 years of experience) • Familiarity with task management tools (e.g., Jira, Azure DevOps) - ( 2 years of experience) • Proficiency in databases, including SQL, NoSQL and vector databases – ( 2 + years of experience) • Working knowledge of ML pipelines and CI/CD. • Experience with at least one of the cloud platforms (Azure, AWS, GCP) - ( 2 + years of experience) Core Excellence Areas (CEA): Candidates must have a strong understanding of fundamentals and good hands-on expertise in at least THREE of the following areas (mention your areas while applying): NLP Generative AI (NLP) Computer Vision Time Series Forecasting Recommendation Systems and Optimization Roles & Responsibilities: • Advanced AI/ML/Gen AI Implementation: o Leverage advanced AI and machine learning techniques to address complex business challenges. o Design, develop, and deliver innovative data science solutions. • Architectural Design: o Develop end-to-end generative AI solutions. o Build scalable architectures for AI/ML models and applications. • Team Leadership: o Lead and mentor a team of data scientists, fostering professional growth and technical excellence. o Provide strategic and technical guidance to ensure the team delivers high-quality projects. • Cross-functional Collaboration: o Work closely with data engineering, product, and business teams to align on objectives and integrate solutions. • Client Engagement : Maintain high levels of client satisfaction through excellent communication, delivering impactful solutions, and building strong relationships. • Innovation: Ideate and implement new approaches for products and solutions, ensuring they stay at the forefront of technology. Nice to have Skills: • Hands-on experience with PySpark, large-scale data processing using distributed frameworks and parallel processing. • Hands-on experience with Azure AI stack, ETL processes, and integration with analytics tools (e.g., Power BI, Tableau) • Knowledge of deep learning frameworks (e.g., PyTorch, TensorFlow, Keras). • Experience with cloud platforms and MLOps practices. • Project management skills to lead initiatives effectively. • Knowledge of graph-based query languages (e.g., Cypher, Gremlin) and Proficiency in graph databases. Experience & Educational Qualifications: • Minimum of 5+ years of experience solving complex machine learning problems. • At least 2+ years of hands-on experience in each of the chosen Core Excellence Areas. • Minimum of 1 year leading and managing ML projects end-to-end. • Bachelor’s degree in computer science, Data Science, or related field (Master’s/PG in AI/ML/DS preferred).

About Us: Planful is the pioneer of financial performance management cloud software. The Planful platform, which helps businesses drive peak financial performance, is used around the globe to streamline business-wide planning, budgeting, consolidations, reporting, and analytics. Planful empowers finance, accounting, and business users to plan confidently, close faster, and report accurately. More than 1,500 customers, including Bose, Boston Red Sox, Five Guys, Grafton Plc, Gousto, Specialized and Zappos rely on Planful to accelerate cycle times, increase productivity, and improve accuracy. Planful is a private company backed by Vector Capital, a leading global private equity firm. Learn more at planful.com . About the Role: We are looking for self-driven, self-motivated, and passionate technical experts who would love to join us in solving the hardest problems in the EPM space. If you are capable of diving deep into our tech stack to glean through memory allocations, floating point calculations, and data indexing (in addition to many others), come join us. Requirements: 5+ years in a mid-level Python Engineer role, preferably in analytics or fintech. Expert in Python (Flask, Django, pandas, NumPy, SciPy, scikit-learn) with hands-on performance tuning. Familiarity with AI-assisted development tools and IDEs (Cursor, Windsurf) and modern editor integrations (VS Code + Cline). Exposure to libraries supporting time-series forecasting. Proficient in SQL for complex queries on large datasets. Excellent analytical thinking, problem-solving, and communication skills. Nice to have: Shape financial time-series data: outlier detection/handling, missing-value imputation, techniques for small/limited datasets. Profile & optimize Python code (vectorization, multiprocessing, cProfile). Monitor model performance and iterate to improve accuracy. Collaborate with data scientists and stakeholders to integrate solutions. Why Planful Planful exists to enrich the world by helping our customers and our people achieve peak performance. To foster the best in class work were so proud of, we’ve created a best in class culture, including: 2 Volunteer days, Birthday PTO, and quarterly company Wellness Days 3 months supply of diapers and meal deliveries for the first month of your Maternity/Paternity leave Annual Planful Palooza, our in-person, company-wide culture Company-wide Mentorship program with Executive sponsorship of CFO and Manager-specific monthly training programs Employee Resource Groups such as Women of Planful, LatinX at Planful, Parents of Planful, and many We encourage our teammates to bring their authentic selves to the team, and have full support in creating new ERGs & communities along the way.

About Us: Celebal Technologies is a leading Solution Service company that provide Services the field of Data Science, Big Data, Enterprise Cloud & Automation. We are at the forefront of leveraging cuttingedge technologies to drive innovation and enhance our business processes. As part of our commitment to staying ahead in the industry, we are seeking a talented and experienced Data & AI Engineer with strong Azure cloud competencies to join our dynamic team. 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

: Job Title: AI Lead , VP LocationPune, India Role Description Engineer is responsible for managing or performing work across multiple areas of the bank's overall IT Platform/Infrastructure including analysis, development, and administration. It may also involve taking functional oversight of engineering delivery for specific departments. Work includes: Planning and developing entire engineering solutions to accomplish business goals Building reliability and resiliency into solutions with appropriate testing and reviewing throughout the delivery lifecycle Ensuring maintainability and reusability of engineering solutions Ensuring solutions are well architected and can be integrated successfully into the end-to-end business process flow Reviewing engineering plans and quality to drive re-use and improve engineering capability Participating in industry forums to drive adoption of innovative technologies, tools and solutions in the Bank. Deutsche Banks Corporate Bank division is a leading provider of cash management, trade finance and securities finance. We complete green-field projects that deliver the best Corporate Bank - Securities Services products in the world. Our team is diverse, international, and driven by shared focus on clean code and valued delivery. At every level, agile minds are rewarded with competitive pay, support, and opportunities to excel. You will work as part of a cross-functional agile delivery team. You will bring an innovative approach to software development, focusing on using the latest technologies and practices, as part of a relentless focus on business value. You will be someone who sees engineering as team activity, with a predisposition to open code, open discussion and creating a supportive, collaborative environment. You will be ready to contribute to all stages of software delivery, from initial analysis right through to production support. What well offer you 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Accident and Term life Insurance Your key responsibilities Proven ability to design, build, and deploy end-to-end AI/ML systems in production. Expertise in data science , including statistical analysis, experimentation, and data storytelling. Experienced in working with large-scale, real-world datasets for model training and analysis. Comfortable navigating urgency, ambiguity, and fast-changing priorities . Skilled at solving complex ML problems independently , from idea to implementation. Strong leadership experience building and guiding high-performing AI teams . Hands-on with deep learning, NLP, LLMs , and classical ML techniques. Fluent in model experimentation, tuning, optimisation , and evaluation at scale. Solid software engineering background and comfort working with data and full-stack teams . Experience with cloud platforms (GCP, AWS, Azure) and production-grade ML pipelines. Bias for action willing to jump into code, data, or ops to ship impactful AI products . Your skills and experience PhD in Computer Science, Data Science, Machine Learning, AI, or a related field. Strong programming skills in Python (preferred), with experience in Java, Scala, or Go a plus. Deep expertise with ML frameworks like TensorFlow, PyTorch, Scikit-learn. Experience with large-scale datasets , distributed data processing (e.g. Spark, Beam, Airflow). Solid foundation in data science statistical modeling, A/B testing, time series, and experimentation. Proficient in NLP, deep learning , and working with transformer-based LLMs . Experience with MLOps practices CI/CD, model serving, monitoring, and lifecycle management. Hands-on with cloud platforms (GCP, AWS, Azure) and tools like Vertex AI, SageMaker, or Databricks. Strong grasp of API design , system integration, and delivering AI features in full-stack products. Comfortable working with SQL/NoSQL , and data warehouses like BigQuery or Snowflake. Familiar with ethical AI, model explainability , and secure, privacy-aware AI development How well support you

Management Level: Ind&Func AI Decision Science Consultant Job Location: Bangalore / Gurgaon Must-have Skills: Excellent understanding of Pharma data sets commercial, clinical, Leverage ones hands on experience of working across one or more of these areas such as real-world evidence data, Statistical Models/Machine Learning including Segmentation & predictive modeling, hypothesis testing, multivariate statistical analysis, time series techniques, and optimization. Good-to-have Skills: Programming languages such as R, Python, SQL, Spark, AWS, Azure, or Google Cloud for deploying and scaling language models, Data Visualization tools like Tableau, Power BI. Job Summary This role involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. Provide strategic advisory services, conduct market research, and develop data-driven recommendations to enhance business performance. Key Responsibilities An opportunity to work on high-visibility projects with top Pharma clients around the globe. Personalized training modules to develop your strategy & consulting acumen to grow your skills, industry knowledge, and capabilities. Provide Subject matter expertise in various sub-segments of the LS industry. Support delivery of small to medium-sized teams to deliver consulting projects for global clients. Responsibilities may include strategy, implementation, process design, and change management for specific modules. Work with the team or as an Individual contributor on the project assigned which includes a variety of skills to be utilized from Data Engineering to Data Science Develop assets and methodologies, point-of-view, research, or white papers for use by the team and the larger community. Acquire new skills that have utility across industry groups. Support strategies and operating models focused on some business units and assess likely competitive responses. Also, assess implementation readiness and points of greatest impact. Additional Information Proficient in Excel, MS Word, PowerPoint, etc. Ability to solve complex business problems and deliver client delight. Strong writing skills to build points of view on current industry trends. Good communication, interpersonal, and presentation skills About Our Company | Accenture (do not remove the hyperlink) Qualification Experience: Proven experience (4+ years) in working on Life Sciences/Pharma/Healthcare projects and delivering successful outcomes. Educational Qualification: Bachelors or Masters degree in Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems, or other Quantitative field.

Management Level: Ind&Func AI Decision Science Consultant Job Location: Bangalore / Gurgaon Must-have Skills: Excellent understanding of Pharma data sets commercial, clinical, Leverage ones hands on experience of working across one or more of these areas such as real-world evidence data, Statistical Models/Machine Learning including Segmentation & predictive modeling, hypothesis testing, multivariate statistical analysis, time series techniques, and optimization. Good-to-have Skills: Programming languages such as R, Python, SQL, Spark, AWS, Azure, or Google Cloud for deploying and scaling language models, Data Visualization tools like Tableau, Power BI. Job Summary This role involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions. Provide strategic advisory services, conduct market research, and develop data-driven recommendations to enhance business performance. Key Responsibilities An opportunity to work on high-visibility projects with top Pharma clients around the globe. Personalized training modules to develop your strategy & consulting acumen to grow your skills, industry knowledge, and capabilities. Provide Subject matter expertise in various sub-segments of the LS industry. Support delivery of small to medium-sized teams to deliver consulting projects for global clients. Responsibilities may include strategy, implementation, process design, and change management for specific modules. Work with the team or as an Individual contributor on the project assigned which includes a variety of skills to be utilized from Data Engineering to Data Science Develop assets and methodologies, point-of-view, research, or white papers for use by the team and the larger community. Acquire new skills that have utility across industry groups. Support strategies and operating models focused on some business units and assess likely competitive responses. Also, assess implementation readiness and points of greatest impact. Additional Information Proficient in Excel, MS Word, PowerPoint, etc. Ability to solve complex business problems and deliver client delight. Strong writing skills to build points of view on current industry trends. Good communication, interpersonal, and presentation skills About Our Company | Accenture (do not remove the hyperlink) Qualification Experience: Proven experience (4+ years) in working on Life Sciences/Pharma/Healthcare projects and delivering successful outcomes. Educational Qualification: Bachelors or Masters degree in Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems, or other Quantitative field.

About the role: This is a unique opportunity to join our fast-growing Data Science team. In the role of Data Scientist, you will execute large scale, high impact data modeling projects with responsibility for designing, developing, validating, socializing, operationalizing, and maintaining data-driven analytics that provide business insights to increase operational efficiency and customer value. What you will do: Deliver modeling and analytical insights to inform strategic and operational initiatives Conduct all phases of the model development process. Including: Understanding business issues, proposing technical solutions, data wrangling, data cleaning, data analysis, feature engineering, model selection, model development, model validation, model operationalization, presentation of results and insights, model implementation, model documentation Convert top-down business initiative requirements into actionable data analytics projects as well as conceiving and proposing a bottom-up analytics innovations Communicate technical solutions and results to business stakeholders Partner with business stakeholders, IT and lead the design and delivery ML solutions Inject the most applicable technology, including Machine Learning, Artificial Intelligence, Natural Language Processing and Statistical Modeling Continuously innovate with state of art techniques to improve the model What you will need: For Data Scientist 3-6 years & for Associate Data Scientist 1-3 years of experience in solving real life business problems using ML & Data Science Bachelor's degree is required. Master's degree preferred. Technical degrees with a concentration in statistics, data science, computer science or related field preferred In-depth knowledge of statistical methods & principles and its usage in the model building & data analysis Experience in applying descriptive, predictive, prescriptive models & data visualization to solve real life business problems Understanding of NLP concepts and its application is preferred Expertise in Python, SQL, Spark Experience with multiple modeling techniques such as: Time Series, Random Forests, Clustering, Neural Networks, Generalized Linear Models, Optimization, DOE, Dimensionality Reduction MLOps experience is preferred (implementing models/algorithms into production systems) Ability to work in a fast-paced environment and deliver against milestones Excellent communication skills in technical and business domains Proven ability to influence key stakeholders and leaders What you will get: Competitive salary, generous paid time off policy, charity match program, Group Medical Insurance, Parental Leave, Employee Assistance Program (EAP) and more! Collaborative, team-oriented culture that embraces diversity Professional development and unlimited growth opportunities

About the Role In this role you will work closely with product, engineering and sales teams to drive the use of Data Science across the Verve Group, collaborate with our audience-focused Data Science team and with the Machine Learning Engineers to engineer prototypes into solutions. What You Will Do DOMAIN In this role your main focus would be on our Ad-Exchange Optimization projects Win Price Prediction in various auctions setups - 1st price, 2nd price, Waterfall Supply forecasting Modeling time dependent supply availability Demand forecasting — Modeling time dependent demand interest Inventory valuation — Assessing true value of inventory in open market Traffic Shaping — Time dependent supply and demand matching Research and Development Our Data Science role includes the following responsibilities: Research and development of cutting edge Machine Learning systems, models, and schemes in many different areas of Adtech Develop real-time algorithms for campaign and bidding optimization Discover insights/patterns in exchange data Design experiments, oversee A/B testing, evaluate the quality of derived assets and continuously monitor model performance Create proof of concepts and data science prototypes Search and select appropriate data sets Perform statistical analysis and use results to improve models Identify differences in data distribution that could affect model performance in real-world situations Visualize data for deeper insights Analyze the use cases of ML algorithms and ranking them by their success probability Understanding when your findings can be applied to business decisions Reducing business problems into optimization problems Verifying data quality Job requirements What You Will Bring 5+ years experience working as a Data Scientist in industry (preferably in advertising) is a must A postgraduate degree in a relevant quantitative field (e.g. applied mathematics, statistics, engineering, computer science, physics, operations research, economics, behavioral sciences). PhD is a strong plus, Fluent in statistical analysis, data mining, and machine learning, Proficient in Python, SQL, PySpark, TensorFlow, Sklearn, Enthusiasm for solving interesting problems, Willingness to learn and work in a team-oriented and constantly changing environment. Nice to have Previous experience in - Auction optimization - Highly imbalanced classification problems - Game theory - Time series forecasting - State-space modeling - Function-Approximation Algorithms What we also work with We work with a wide range of tools, technologies and processes. The right candidate should have willingness to learn new technologies. In this role is you will get hands-on experience with many established and emerging technologies: Technologies: GCP and AWS, BigQuery, DevOps tooling: CI/CD, Docker, Airflow, Kubernetes, Grafana, Jupyterhub Other: Challenging constraints (high volume, low latency), Integrating with high performance technologies, Efficient work with Big Data (wrangling, modeling, low latency inference), Developing data-driven products.

We are looking for a Senior Data Scientist who is passionate about solving complex business problems using data. The ideal candidate will have strong hands-on experience in Python , SQL , and advanced machine learning algorithms , along with domain expertise in forecasting , pricing optimization , or inventory planning . You will work closely with cross-functional teams including product, engineering, and business stakeholders to drive data-driven strategies. Key Responsibilities: Design, build, and deploy predictive and optimization models for use cases such as demand forecasting , dynamic pricing , or inventory optimization . Translate business problems into analytical frameworks and provide actionable insights. Build and maintain scalable data pipelines and model workflows using Python and SQL. Collaborate with data engineers to ensure model integration into production systems. Present findings and recommendations to leadership using data visualizations and storytelling. Stay current with the latest techniques in machine learning , statistics , and operations research . Lead and mentor junior data scientists and analysts when required. Required Skills and Experience: 5+ years of experience in a Data Science or Analytics role with a strong business impact. Strong programming skills in Python (pandas, scikit-learn, statsmodels, etc.). Proficiency in SQL for data extraction, transformation, and manipulation. Deep understanding of machine learning algorithms (regression, classification, clustering, time series forecasting). Experience with one or more of the following domains: Demand Forecasting Price Optimization Inventory Optimization / Supply Chain Analytics Strong problem-solving and quantitative skills. Experience working with large datasets and distributed computing tools (e.g., Spark, Hadoop) is a plus. Familiarity with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn). Preferred Qualifications: Masters or PhD in Computer Science, Statistics, Mathematics, Economics, Operations Research, or a related field. Experience in retail, e-commerce, manufacturing, or logistics is a strong plus. Exposure to optimization libraries (e.g., PuLP, OR-Tools, Gurobi) is a bonus. Experience deploying models using MLOps tools or platforms is a plus

Invent, implement and deploy state-of-the-art machine learning and/or specific domain industry algorithms and systems. Build prototypes and explore conceptually new solutions. Work collaboratively with science, engineering, and product teams to identify customer needs in order to create and implement solutions, promote innovation and drive model implementations. Applies data science capabilities and research findings to create and implement solutions to scale. Responsible for developing new intelligence around core products and services through applied research on behalf of our customers. Develops models, prototypes, and experiments that pave the way for innovative products and services. Build cloud services that work out of the box for enterprises, e.g. decision support, anomaly detection, forecasting and recommendations), natural language processing (NLP), Natural Language Understanding (NLU),Time Series, Automatic Speech Recognition (ASR), Machine Learning (ML), and Computer Vision (CV). Design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. Conversant on ethical problems in consideration of sciences. Responsibilities Drives and plans implementation of company policy for achieving business goals. Defines the bar for science practices, and helps teams achieve those goals. Identifies and mitigates risks across full set of systems, particularly at the intersection of business and engineering. Innovate AI and ML powered solutions (rich APIs, ML models and end to end services) with strategic ISVs and customers. Develop deep product intuition to influence future product roadmaps and drive decision making. Clearly articulate technical work to audiences of all levels and across multiple functional areas in both internal and external settings. Engage in forward looking research both internal and with academic institutions globally. Hires and mentors across the org. Perform an active role in team planning, review and retrospective events. Ensures experiments are ready for hand-off to Software Developers ship into production. May perform other duties as assigned.

In this role, you will be required to build and develop advanced analytics capabilities and assets/accelerators. You will be responsible for all aspects of end-to-end Workforce Management capability creation, including Operations (forecasting, capacity planning, staffing, scheduling, real-time monitoring, and operations management reporting and analysis), Software Configuration, as well as Insight generation. It will be your responsibility to build and update Standard Operating Procedures (SOPs) for Workforce Management with appropriate participation from multiple Operations and Analytics teams. You will need to develop a forecasting, capacity planning, and scheduling strategy and framework that will enable the company to meet service levels, revenue goals, and operating parameters. You will own the workforce management team as they balance schedule adjustments, exceptions, adherence, mentorship, feedback, and training schedules. Additionally, you will evaluate the accuracy of forecasts and schedules prepared by the WFM team and act as the primary point of contact for data engineers to manage data effectively. You are required to have a Bachelors or Masters degree in a quantitative discipline such as Commerce, Statistics, Actuarial Sciences, Mathematics, Quantitative Finance, or Economics. Strong analytical skills with a solid understanding of statistics and predictive modeling are essential. Excellent knowledge of Contact center Operations is a must, and proficiency in the use of Dialer, workforce management software, CMS reporting, call recording, and monitoring systems is required. Demonstrating knowledge of call center metrics and WFM policies and procedures is essential. Experience in predictive modeling techniques such as GLM, Linear Regression, Time Series, Segmentation/Cluster Analysis, Decision Trees, and Random Forests is a must. Advanced proficiency with Microsoft Excel, including VBA, is required, along with basic database skills including SQL and the ability to pull together disparate data sources. Knowledge of statistical tools like R, SAS, SPSS, etc., is preferred. Analytical skills to provide insights on data trends and patterns critical to the business are necessary. Project/Program Management knowledge, including working on Architecture/Design of BI/Analytics solutions, is beneficial. You should have the ability to establish priorities, handle multiple assignments concurrently with minimal direction in a fast-paced work environment, and work both independently and as part of a team. Being self-disciplined and results-oriented are key qualities for this role. Preferred qualifications/skills include working knowledge of data entry and extraction through Verint/Genesis/NICE, understanding of scheduling functionality and forecasting through Verint/Genesis/NICE, and knowledge of real-time analysis using Verint/Genesis/NICE.,

As an experienced data analytics professional with 1 to 2 years of experience, you will be responsible for developing and implementing data analytics methodologies. Your role will require good interpersonal skills along with excellent communication abilities. Your technical skills must include proficiency in Python, machine learning, deep learning, data wrangling, and integration with Big Data tools such as Hadoop, Scoop, Impala, Hive, Pig, and Spark R. You should also have a solid understanding of statistics, data mining, algorithms, time series analysis, forecasting, SQL queries, and Tableau data visualization. Having a good grasp of technologies like Hadoop, HBase, Hive, Pig, Mapreduce, Python, R, Java, Apache Spark, Impala, and machine learning algorithms is essential for this role. Your responsibilities will involve developing training content on Big Data and Hadoop technologies for students, working professionals, and corporates. You will conduct both online and classroom training sessions, provide practical use cases and assignments, and design self-paced recorded training sessions. It's important to continuously enhance teaching methodologies for an effective online learning experience and work collaboratively in small teams to make a significant impact. You will be tasked with designing and overseeing the development of real-time projects to provide practical exposure to the trainees. Additionally, you may work as a consultant or architect in developing and training real-time Big Data applications for corporate clients either on a part-time or full-time basis. Hands-on knowledge of tools like Anaconda Navigator, Jupyter Notebook, Hadoop, Hive, Pig, Mapreduce, Apache Spark, Impala, SQL, and Tableau will be required to excel in this role.,

As a member of ClearTrail, you will be part of a team where work transcends beyond being just a job. Our mission is to create solutions that empower those committed to ensuring the safety of individuals, locations, and communities. With over 23 years of experience, law enforcement and federal agencies worldwide rely on ClearTrail as their dedicated partner in protecting nations and enhancing lives. We are at the forefront of shaping the future of intelligence gathering through the development of artificial intelligence and machine learning-based solutions for lawful interception and communication analytics. Our focus is on addressing the world's most complex challenges by leveraging cutting-edge technologies. Your primary responsibility will involve developing and training machine learning models that integrate drone, satellite, and real-time video data to achieve advanced visual comprehension. Key tasks include building ML/DL models for image and video classification, segmentation, and spatiotemporal analysis, as well as creating fusion methods to align and merge satellite, drone, and ground footage. You will be expected to apply various techniques such as multi-scale learning, temporal modeling (e.g., 3D CNNs, transformers), and sensor fusion, along with conducting model evaluation and optimization across diverse data sources. To excel in this role, you must possess strong Python programming skills and proficiency in data manipulation using libraries like NumPy, Pandas, and SciPy. Additionally, you should be well-versed in vision/model libraries such as MMDetection, Detectron2, and OpenCV, and have experience in deep learning frameworks like PyTorch and TensorFlow, particularly in video models like TimeSformer, SlowFast, I3D, and Yolo. Familiarity with satellite/drone geospatial fusion, GPS/IMU metadata, scene alignment, time series analysis, motion tracking, and optical flow techniques will be advantageous. Knowledge of remote sensing libraries like Rasterio, GDAL, GeoPandas, and xarray will also be beneficial for this role. Join us at ClearTrail and be part of a dynamic team dedicated to creating innovative solutions that make a real difference in the world of intelligence and security.,

The Model Risk Management (MRM) team at ICE is seeking a Risk Analyst to join their global Enterprise Risk Management function. As a Risk Analyst, you will collaborate with the MRM team to independently validate quantitative models used across ICE's business units. Your role will involve communicating testing results within the group and beyond, as well as providing targeted analytics services for financial risk models. By applying statistical, mathematical, and computational methods, you will ensure that models are aligned with their design objectives and business applications. Your responsibilities will include validating and supporting models, methodologies, and risk reporting across the organization. You will analyze validation reports, extract meaningful insights from data, and craft a cohesive narrative to communicate the findings effectively. Additionally, you will document methods, techniques, and results meticulously, ensuring the clarity, consistency, and accuracy of model validation reports. Engaging with stakeholders, you will deliver presentations of analytical findings and identify opportunities for report enhancements and automation. To qualify for this role, you should hold a Master's degree or higher in Economics, Finance, Statistics, Mathematics, or a related field. Strong analytical and problem-solving skills are essential, along with a deep understanding of statistical concepts such as descriptive statistics, data visualization, probability, and linear models. Proficiency in programming languages like Python or R, as well as SQL, is required. Moreover, excellent presentation, verbal communication, and business writing skills are necessary, along with demonstrated expertise in data exploration and critical thinking. Preferred qualifications for the position include at least 2 years of experience in financial/economic data analysis. Additionally, progress towards industry certifications like FRM and CFA, as well as familiarity with Tableau for visual analytics, would be advantageous. Join the MRM team at ICE to contribute to model validation and risk management practices, while continuously seeking opportunities for improvement and innovation.,

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. At Target, we have a timeless purpose and a proven strategy, and that hasn't happened by accident. Some of the best minds from diverse backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target's global team and has more than 4,000 team members supporting the company's global strategy and operations. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values diverse backgrounds. We believe your unique perspective is important, and you'll build relationships by being authentic and respectful. At Target, inclusion is part of the core value. We aim to create equitable experiences for all, regardless of their dimensions of difference. As an equal opportunity employer, Target provides diverse opportunities for everyone to grow and win. The People Analytics team's mission is to empower a data-driven approach to HR and people decisions regarding our global workforce. We are uniquely positioned to provide unbiased insights to unlock value and drive outcomes and to enable and influence HR and business strategy. The People Analytics team integrates into the business as strategic HR analytics partners and anticipates and uncovers stated or unstated needs. They use analytics expertise to test, measure, analyze, understand, and answer various business questions. The team provides reporting to help inform on the current state of the business and help facilitate processes at scale. They connect understanding across business and HR to deliver data-driven products and solutions, providing meaningful insights and recommendations. About the role: Our Data Analysts are expected to explore data, technologies, and the application of mathematical techniques to enable business insights. Data analysts accomplish this through a wide variety of skills including data wrangling, reporting, dashboarding, visualization, statistical analysis, modeling, and the presentation of recommendations and insight. Analysts work within an agile environment, which requires active participation in ceremonies to accomplish the team's goals. They also develop domain knowledge as they learn about their business area and support applying key data management principles like metadata management, data profiling, and documenting data lineage. Key Responsibilities: - Actively explore data for specific use cases. - Develop expertise in business domain and processes. - Create measurable insights from the data to be shared. - Develop metrics, measurement strategy, reports, and statistics. - Document calculations, code, and adhere to data management principles. - Validate and test data assets of others in the form of peer review. - Explore statistical analysis that could be applied to the data. - Perform descriptive statistics including mean, variance, median, correlation. - Apply insights and testing in partnership with business users. - Be an active participant in team meetings. - Lead agile ceremonies. - Ability to work independently to turn business problems into data solutions. - Serve as a thought leader and mentor on business domain and analytical techniques to elevate team performance. Qualifications: - BA/BS or equivalent experience. - 9+ years" work experience in data analysis or master's level education in business analytics, data science, etc. - Demonstrated leader in knowledge and application of data, reporting, and analytics. - Proficient with various programming languages - SQL, R, Python. - Proficient with relational and non-relational databases. - Strong domain-specific knowledge in Human Resources data and processes. - Prior experience in human resources or talent/people analytics industry. - Strong mathematical and statistical skills. - Excellent communication skills with the ability to speak to both business and technical teams. - Knowledge of AB Testing methods, time series, S&OP planning, Forecasting models, and analytics tools such as SQL, Excel, Hadoop, Hive, Spark, Python, R, Domo, Adobe Analytics, and/or equivalent technologies.,

As a Manager, Behavioral Modeler (Development/Validation) & Researcher Specialist at Genpact, you will be responsible for developing or validating Behavioral Models for banking and financial institutions, focusing on areas such as Financial Crime (Fraud or AML), Marketing Campaigns, and Adjudication models. Your role will involve working closely with the centralized advanced analytics team of banking or financial firms, interacting with various business units, auditors, and model development/validation teams to ensure compliance with Enterprise Modeling Governance standards. Your key responsibilities will include providing analytical support to mitigate risk, assessing data quality for model development, developing machine learning-based models, proposing recommendations to improve monitoring systems, conducting in-depth research on behavioral modeling policies, and contributing to the creation of whitepapers and artifacts. You will be expected to have hands-on experience in developing and validating models, risk management, and applying AI, ML, and Deep Learning techniques using tools such as SAS, Python, and R. The qualifications we seek in you include a Master's degree in a quantitative discipline, experience in statistical modeling, detailed knowledge of data analysis techniques, expertise in SQL, ETL, and strong scripting and automation skills. Additionally, you should possess strong client management, communication, and presentation skills, be self-driven, proactive, and have the ability to work under ambiguity and with minimal supervision. You should also have strong project management experience, the ability to lead projects and teams, and demonstrate expertise in communicating and coordinating across multiple business units. Preferred qualifications/skills include strong networking, negotiation, and influencing skills, as well as prior experience in financial crime and machine learning models. If you are a forward-thinking individual with a hunger for learning and a passion for turning innovative ideas into reality, we invite you to apply for this challenging and rewarding role at Genpact. Please note that this is a full-time position based in India-Kolkata, and the job posting was on Oct 7, 2024.,

Title: AI/ML Architect Location: Onsite Bangalore Experience: 10+ years Position Summary: We are seeking an experienced AI/ML Architect to lead the design and deployment of scalable AI solutions. This role requires a strong blend of technical depth, systems thinking, and leadership in machine learning , computer vision , and real-time analytics . You will drive the architecture for edge, on-prem, and cloud-based AI systems, integrating 3rd party data sources, sensor and vision data to enable predictive, prescriptive, and autonomous operations across industrial environments. Key Responsibilities: Architecture & Strategy Define the end-to-end architecture for AI/ML systems including time series forecasting , computer vision , and real-time classification . Design scalable ML pipelines (training, validation, deployment, retraining) using MLOps best practices. Architect hybrid deployment models supporting both cloud and edge inference for low-latency processing. Model Integration Guide the integration of ML models into the IIoT platform for real-time insights, alerting, and decision support. Support model fusion strategies combining disparate data sources, sensor streams with visual data (e.g., object detection + telemetry + 3rd party data ingestion). MLOps & Engineering Define and implement ML lifecycle tooling, including version control, CI/CD, experiment tracking, and drift detection. Ensure compliance, security, and auditability of deployed ML models. Collaboration & Leadership Collaborate with Data Scientists, ML Engineers, DevOps, Platform, and Product teams to align AI efforts with business goals. Mentor engineering and data teams in AI system design, optimization, and deployment strategies. Stay ahead of AI research and industrial best practices; evaluate and recommend emerging technologies (e.g., LLMs, vision transformers, foundation models). Must-Have Qualifications: Bachelor’s or Master’s degree in Computer Science, AI/ML, Engineering, or a related technical field. 8+ years of experience in AI/ML development, with 3+ years in architecting AI solutions at scale. Deep understanding of ML frameworks (TensorFlow, PyTorch), time series modeling, and computer vision. Proven experience with object detection, facial recognition, intrusion detection , and anomaly detection in video or sensor environments. Experience in MLOps (MLflow, TFX, Kubeflow, SageMaker, etc.) and model deployment on Kubernetes/Docker . Proficiency in edge AI (Jetson, Coral TPU, OpenVINO) and cloud platforms (AWS, Azure, GCP). Nice-to-Have Skills: Knowledge of stream processing (Kafka, Spark Streaming, Flink). Familiarity with OT systems and IIoT protocols (MQTT, OPC-UA). Understanding of regulatory and safety compliance in AI/vision for industrial settings. Experience with charts, dashboards, and integrating AI with front-end systems (e.g., alerts, maps, command center UIs). Role Impact: As AI/ML Architect, you will shape the intelligence layer of our IIoT platform — enabling smarter, safer, and more efficient industrial operations through AI. You will bridge research and real-world impact , ensuring our AI stack is scalable, explainable, and production-grade from day one.

We are looking for an experienced Senior Data Engineer to lead the development of scalable AWS-native data lake pipelines with a strong focus on time series forecasting and upsert-ready architectures. This role requires end-to-end ownership of the data lifecycle, from ingestion to partitioning, versioning, and BI delivery. The ideal candidate must be highly proficient in AWS data services, PySpark, versioned storage formats like Apache Hudi/Iceberg, and must understand the nuances of data quality and observability in large-scale analytics systems. Role & responsibilities Design and implement data lake zoning (Raw Clean Modeled) using Amazon S3, AWS Glue, and Athena. Ingest structured and unstructured datasets including POS, USDA, Circana, and internal sales data. Build versioned and upsert-friendly ETL pipelines using Apache Hudi or Iceberg. Create forecast-ready datasets with lagged, rolling, and trend features for revenue and occupancy modelling. Optimize Athena datasets with partitioning, CTAS queries, and metadata tagging. Implement S3 lifecycle policies, intelligent file partitioning, and audit logging. Build reusable transformation logic using dbt-core or PySpark to support KPIs and time series outputs. Integrate robust data quality checks using custom logs, AWS CloudWatch, or other DQ tooling. Design and manage a forecast feature registry with metrics versioning and traceability. Collaborate with BI and business teams to finalize schema design and deliverables for dashboard consumption. Preferred candidate profile 9-12 years of experience in data engineering. Deep hands-on experience with AWS Glue, Athena, S3, Step Functions, and Glue Data Catalog. Strong command over PySpark, dbt-core, CTAS query optimization, and partition strategies. Working knowledge of Apache Hudi, Iceberg, or Delta Lake for versioned ingestion. Experience in S3 metadata tagging and scalable data lake design patterns. Expertise in feature engineering and forecasting dataset preparation (lags, trends, windows). Proficiency in Git-based workflows (Bitbucket), CI/CD, and deployment automation. Strong understanding of time series KPIs, such as revenue forecasts, occupancy trends, or demand volatility. Data observability best practices including field-level logging, anomaly alerts, and classification tagging. Experience with statistical forecasting frameworks such as Prophet, GluonTS, or related libraries. Familiarity with Superset or Streamlit for QA visualization and UAT reporting. Understanding of macroeconomic datasets (USDA, Circana) and third-party data ingestion. Independent, critical thinker with the ability to design for scale and evolving business logic. Strong communication and collaboration with BI, QA, and business stakeholders. High attention to detail in ensuring data accuracy, quality, and documentation. Comfortable interpreting business-level KPIs and transforming them into technical pipelines.

Job Title: Data Scientist Turning Data into Decisions Location: Bengaluru | Experience: 25 Years | Type: Full-Time About the Role: Are you passionate about predicting the future with data? Do you thrive on uncovering patterns hidden in time series and driving impactful business decisions? We’re looking for a Data Scientist who’s part analyst, part engineer, and 100% curious. What You’ll Do: Forecast demand like a pro Optimize supply chains and uncover hidden trends Build smart ML models using Python, TensorFlow, or PyTorch Turn messy data into clear, actionable insight Collaborate with teams and tell compelling stories through dashboards Tech Toolkit: Time Series | Regression & A/B Testing Python | NumPy, Pandas, scikit-learn Tableau / Plotly / Matplotlib SQL | ETL Pipelines You’re a Perfect Fit If: You have 2+ years of hands-on Data Science experience You think in models and breathe in data You’re a storyteller with code and charts You love solving problems that make businesses smarter.

Position level: AI Specialist/Software engineering professional (Cant be a junior/fresher, needs to be middle to senior level person) Work Experience: Ideally, 4 to 5 years of working as a Data Scientist / Machine Learning and AI at a managerial position (end-to-end project responsibility). Slightly lower work experience can be considered based on the skill level of the candidate. About the job: Use AI-ML to work with data to predict process behaviors. Stay abreast of industry trends, emerging technologies, and best practices in data science, and provide recommendations for adopting innovative approaches within the product teams. In addition, championing a data-driven culture, promoting best practices, knowledge sharing, and collaborative problem-solving. Abilities: Knowledge about data analysis, Artificial Intelligence (AI), Machine Learning (ML), and preparation of test reports to show results of tests. Strong in communication with a collaborative attitude, not afraid to take responsibility and make decisions, open to new learning, and adapt. Experience with end-to-end process and used to make result presentation to customers. Technical Requirements: Experience working with real world messy data (time series, sensors, etc.) Familiarity with Machine learning and statistical modelling Ability to interpret model results in business context Knowledge of Data preprocessing (feature engineering, outlier handling, etc.) Soft Skill Requirements: Analytical thinking Ability to connect results to business or process understanding Communication skills Comfortable explaining complex topics to stakeholders Structured problem solving – Able to define and execute a structured way to reach results Autonomous working style – can drive a small project or parts of a project Tool Knowledge: Programming: Python (Common core libraries: pandas, numpy, scikit-learn, matplotlib, mlfow etc.); Knowledge of best practices (PEP8, code structure, testing, etc.) Code versioning (GIT) Data Handling: SQL; Understanding of data format (CSV, JSON, Parquet); Familiarity with time series data handling Infrastructure: Basic Cloud technology knowledge (Azure (preferred), AWS, GCP); Basic Knowledge of MLOps workflow Good to have: Knowledge of Azure ML, AWS SageMaker; Knowledge of MLOps best practices in any tool; Containerization and deployment (Docker, Kubernetes) Languages: English – Proficient/Fluent Location: Hybrid (WFO+WFH) + Availability to visit customer sites for meetings and work-related responsibilities as per the project requirement.

Machine Learning Engineer Python, with proficiency in ML libraries such as scikit-learn, TensorFlow, PyTorch Experience: 5+ years Location: Fujitsu India R&D Center Position Type: Full-time | R&D About Fujitsu R&D Fujitsu is a multibillion-dollar global corporation with approximately 124,000 professionals in multiple countries. Fujitsu has served as a trusted partner to the worldwide telecommunications industry for more than 85 years. More information about Fujitsu’s network products can be found at: https://www.fujitsu.com/us/products/network/ Job Summary: We are looking for a Senior Software Engineer – AI/ML with deep expertise in developing and deploying cloud-native machine learning solutions. This role demands strong proficiency in Python-based ML libraries, design of scalable microservices, and deep knowledge of NoSQL databases. The ideal candidate will have hands-on experience with ML algorithms, model performance tuning, model accuracy optimization, and proven delivery of AI applications in areas such as anomaly detection and time series forecasting. You will work closely with data scientists, cloud engineers, and product teams to build intelligent systems that operate at scale and deliver real-time insights into complex, high-volume data. Key Responsibilities: Design, develop, and deploy AI/ML microservices using Python in a cloud-native environment. Build scalable pipelines for training, tuning, and serving ML models in production. Integrate and manage NoSQL databases (e.g., MongoDB, ElasticSearch) for efficient storage and retrieval of unstructured or time-series data. Optimize model accuracy, latency, and throughput, including hyperparameter tuning, feature engineering, and profiling model performance. Lead the development of ML-based solutions for anomaly detection, time series forecasting, and predictive analytics. Collaborate with cross-functional teams to translate product requirements into ML-based features. Apply best practices in model versioning, A/B testing, and continuous training/validation. Ensure high standards of code quality, modularity, and observability in deployed services. Evaluate new tools, technologies, and frameworks for ML lifecycle management and monitoring. Required Skills: 5+ years of experience in backend software development using Python . Strong programming expertise in Python , with proficiency in ML libraries such as scikit-learn, TensorFlow, PyTorch , XGBoost, or LightGBM. Demonstrated experience in implementing anomaly detection algorithms and time series forecasting models (e.g., ARIMA, Prophet, LSTM). Good understanding of AI/ML algorithms like Random Forest, K-Means, Autoencoders, Graph Neural Networks (GNNs), and Louvain for anomaly detection, clustering, and time-series analysis. Experience in building and deploying cloud-native microservices (e.g., on AWS, Azure, GCP). Solid understanding of NoSQL databases like MongoDB, ElasticSearch storing ML data and time series. Messaging bus like Kafka or RabbitMQ Hands-on experience with model performance tuning, evaluation metrics, and real-world ML system optimization. Familiarity with ML lifecycle tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Understanding of containerization and orchestration (Docker, Kubernetes) for scalable deployment. Proficient in working with Git, CI/CD workflows, and Agile development methodologies. Experience with CI/CD tools such as Jenkins, GitLab CI, or GitHub Actions. Familiarity with Agile methodologies and ticketing systems (JIRA). Nice to Have: Experience applying ML to wireless network optimization. Familiarity with federated learning or edge AI techniques to enable distributed ML across radio/access nodes. Understanding of online learning or reinforcement learning for dynamic network adaptation and control. Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.