3 Timeseries Models Jobs

The Analytics & Information Management team at Citi is seeking an Anti Money Laundering (AML) Independent Validation (IV) analyst to join the team in Bangalore. As an IV analyst, you will be responsible for conducting independent validation on AML scenarios, statistical analysis, data visualizations, and data processing in alignment with global standards and regulatory guidelines. Your role will involve presenting findings clearly both in written reports and verbally to stakeholders. To excel in this role, you should have a background in statistics and/or mathematics, with experience in data analysis and data mining being advantageous. Fluency in English, strong communication skills, and the ability to create formal statistical documentation are essential. Knowledge of banking, finance, and AML practices is preferred. Key responsibilities include performing independent validation of AML scenarios, applying statistical methods to analyze data, presenting validation outcomes to stakeholders, extracting and reporting data from databases, and ensuring data quality and reliability. Additionally, you will be expected to conduct annual performance assessments and contribute to process improvements. The ideal candidate will have 3-5 years of experience in the analytics industry, previous experience in financial services, familiarity with AML monitoring systems, and proficiency in tools such as SAS, SQL, Python, Excel, and VBA. A basic understanding of Big Data/Hadoop architecture, segmentation, clustering techniques, and statistical models is desirable. Strong analytical skills, the ability to work well in a team, and a proactive attitude towards innovation are also important qualities for this role. If you possess a Master's degree in a numerate subject and meet the qualifications mentioned above, we encourage you to apply for this full-time position with Citi. Join us in our commitment to diversity and equal opportunity in the workplace.,

Job Description: As a Data Scientist - Deputy Manager, your primary responsibility will be to implement solutions to problems using data analysis, data mining, optimization tools, and machine learning techniques combined with statistics. You will be tasked with building data-science and technology-based algorithmic solutions to address various business needs. In this role, you will design large-scale models utilizing Regression, Linear Models Family, and Time-series models. Additionally, you will be driving the collection of new data and refining existing data sources to enhance analytical capabilities. An essential aspect of your role will involve analyzing and interpreting the results of analytics experiments while applying a global approach to analytical solutions within a specific business area and across the enterprise. You should possess the ability to utilize data for Exploratory, Descriptive, Inferential, Prescriptive, and Advanced Analytics. Furthermore, sharing dashboards, reports, and analytical insights from data will be a key component of your responsibilities. Experience in visualizing large datasets is preferred and considered an added advantage. To excel in this position, you must have experience in solving analytical problems using quantitative approaches and a passion for empirical research aimed at answering challenging questions with data. Your expertise should extend to manipulating and analyzing complex, high-volume, high-dimensionality data from various sources. You should be proficient in applying a flexible analytic approach that yields results at different levels of precision and be able to communicate complex quantitative analysis in a clear, precise, and actionable manner. Technical Knowledge and Skills Required: - Expert knowledge of an analysis tool such as Pyspark and Python - Experience working with large datasets, with familiarity in distributed computing tools like Map/Reduce, Hadoop, Hive, etc. - Understanding of relational databases and SQL You're the right fit if: - Possess 5-8 years of experience in engineering or a related field - Demonstrated experience in solving analytical problems using quantitative approaches - Proficiency in manipulating and analyzing complex, high-volume data from various sources - Ability to apply a flexible analytic approach yielding results at varying levels of precision - Strong communication skills to convey complex quantitative analysis clearly and precisely - Expertise in analysis tools such as R and Python - Familiarity with working on large datasets and distributed computing tools How we work together: We believe in the power of collaboration and teamwork. For our office-based teams, working in-person at least 3 days per week is essential. Different roles may require full-time presence onsite at the company's facilities or in the field, typically at customers" or suppliers" locations. About Philips: Philips is a health technology company dedicated to providing quality healthcare accessible to all. Our mission revolves around the idea that every individual matters, and we are committed to ensuring that everyone receives the healthcare they deserve. Join us in making a difference in the lives of others by contributing to our impactful work. Learn more about our business, explore our vibrant history, and discover our purpose. If you find this role intriguing and possess most, if not all, of the required experiences, we encourage you to apply. You might be the perfect fit for this position or other opportunities at Philips. Learn more about our culture of impactful care and consider becoming part of our team.,

Job Description: Total 2 industry experience 3 year experience in applying machine learning techniques to real business problems Key Responsibilities: Managing large machine learning applications and designing and implementing new frameworks to build scalable and efficient data processing workflows and machine learning pipelines Build the tightly integrated pipeline that optimizes and compiles models and then orchestrates their execution Collaborate with CPU GPU and Neural Engine hardware backends to push inference performance and efficiency Work closely with feature teams to facilitate and debug the integration of increasingly sophisticated models including large language models Automate data processing and extraction Engage with sales team to find opportunities understand requirements and translate those requirements into technical solutions Develop reusable ML models and assets into production Technical Requirements: Excellent Python programming and debugging skills Refer to Pytho JD given below Proficiency with SQL relational databases non relational databases Passion for API design and software architecture Strong communication skills and the ability to naturally explain difficult technical topics to everyone from data scientists to engineers to business partners Experience with modern neural network architectures and deep learning libraries Keras TensorFlow PyTorch Experience unsupervised ML algorithms Experience in Timeseries models and Anomaly detection problems Experience with modern large language model Chat GPT BERT and applications Expertise with performance optimization Experience or knowledge in public cloud AWS services S3 Lambda Familiarity with distributed databases such as Snowflake Oracle Experience with containerization and orchestration technologies such as Docker and Kubernetes Preferred Skills: Technology->Machine Learning->Python,Technology->Big Data - Data Processing->Spark,Technology->Machine Learning->R