6 Sparkpyspark Jobs

As a Senior Data Engineer at Novartis, you will play a pivotal role within the Data & Digital Commercial organization, leading the technical foundation of AI-powered commercial solutions. Your contributions will be instrumental in driving more effective engagement, access, and performance both globally and within local markets. Your responsibilities will include designing, developing, and deploying scalable, production-grade data pipelines for commercial AI products. You will oversee the technical delivery from vendor partners, ensuring high-quality output that aligns with Novartis standards, timelines, and budgets. Acting as a liaison between business stakeholders and engineering teams, you will translate business requirements into actionable data solutions. In this role, you will integrate and harmonize complex data from various sources, including internal systems and third-party providers. Upholding data governance, lineage tracking, and data quality monitoring will be essential to ensure compliance requirements are met. You will also be expected to recommend innovative data engineering solutions that enhance the performance and efficiency of the data infrastructure. Collaboration with AI/ML engineers to ensure data readiness for model training, scoring, and operationalization will be a key aspect of your role. Additionally, you will guide and mentor junior data engineers, contributing to the growth of the commercial data engineering capability within Novartis. To qualify for this position, you should hold a Bachelor's or Master's degree in computer science, engineering, or a related field. With at least 7 years of experience in data engineering, including 2 years in a leadership or delivery oversight role, you should possess strong expertise in Python, SQL, Spark/PySpark, and tools like Databricks, Airflow, Snowflake, and Azure Data Factory. Your ability to manage vendor teams, communicate effectively, and work collaboratively with commercial business leads in pharma or life sciences will be crucial. Experience with pharmaceutical commercial data, knowledge of privacy and compliance frameworks relevant to healthcare data, and familiarity with Agile methodologies are highly desirable. Direct experience in pharma commercial domains, exposure to MLOps workflows, and an understanding of AI-based targeting and segmentation use cases are considered advantageous qualifications. Novartis is dedicated to fostering a diverse and inclusive work environment that reflects the patients and communities it serves. If you require accommodation due to a medical condition or disability, please reach out to the provided contact information for assistance. Join Novartis in reimagining medicine and creating a brighter future together.,

Embark on a transformative journey as a Vice President (VP) Data Scientist specializing in Artificial Intelligence (AI) and Machine Learning (ML) at Barclays within the Group Control Quantitative Analytics team. In this role, you will lead the advancement of the digital landscape, fostering innovation and ensuring exceptional customer experiences through the utilization of cutting-edge technology. The Group Control Quantitative Analytics (GCQA) team is a globally renowned organization comprising highly skilled data scientists dedicated to AI, ML, and Gen AI model development, management, governance, and monitoring. Under the leadership of Lee Gregory, the Chief Data and Analytics Officer (CDAO) in Group Control, Remi Cuchillo leads GCQA. The team is accountable for the creation and oversight of AI/ML/GenAI models, offering analytical support across various domains including Fraud, Financial Crime, Customer Due Diligence, Controls, and Security at Barclays. As a Data Scientist, you will play a pivotal role in developing targeting solutions that seamlessly integrate with existing systems, ensuring optimal performance. Collaborating with the GC CDAO team, you will provide expertise in project design, predictive model development, validation, monitoring, tracking, and implementation. Key Skills for Success: - Proficiency in Python Programming. - Expertise in AI and ML algorithms, including Natural Language Processing (NLP). - Strong command of SQL. - Experience with Spark/PySpark. - Knowledge of Predictive Model development. - Familiarity with model lifecycle management, including monitoring, governance, and implementation. - Proficiency in DevOps tools such as Git/Bitbucket. - Project management skills using JIRA. Highly Valued Skills: - Familiarity with DevOps tools like TeamCity, Jenkins. - Understanding of the Financial/Banking Domain. - Knowledge of GenAI tools and applications. - Experience with AWS and Databricks. Responsibilities: - Design analytics and modeling solutions for complex business challenges. - Collaborate with technology to specify dependencies required for analytical solutions. - Develop high-performing, well-documented analytics and modeling solutions. - Implement analytics and models in stable, well-tested software. - Provide ongoing support to ensure the effectiveness of analytics solutions. - Ensure compliance with Barclays Enterprise Risk Management Policies, especially the Model Risk Policy. - Conduct all development activities within the defined control environment. Vice President Expectations: - Contribute to strategy, drive change recommendations, and manage resources, budgets, and policies. - Demonstrate leadership behaviors to create an environment conducive to colleague growth and excellence. - Provide subject matter expertise and guide technical direction for multi-year projects. - Advise key stakeholders on functional and cross-functional areas. - Manage and mitigate risks to support the governance agenda. - Demonstrate leadership in managing risk and strengthening controls. - Collaborate across different business areas to align with business strategies. - Create innovative solutions based on extensive research and analysis. - Foster relationships with internal and external stakeholders to achieve business objectives. All colleagues are expected to embody the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship, as well as the Barclays Mindset of Empower, Challenge, and Drive.,

Embark on a transformative journey as a Data Scientist AI/ML - AVP at Barclays in the Group Control Quantitative Analytics team, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unparalleled customer experiences. Group Control Quantitative Analytics (GCQA) is a global organization of highly specialized data scientists working on Artificial Intelligence, Machine Learning, and Gen AI model development and model management including governance and monitoring. GCQA is led by Remi Cuchillo under Lee Gregory, who is Chief Data and Analytics Officer (CDAO) in Group Control. GCQA is responsible for developing and managing AI/ML/GenAI models (including governance and regular model monitoring) and providing analytical support across different areas including Fraud, Financial Crime, Customer Due Diligence, Controls, Security, etc. within Barclays. The Data Scientist position provides project-specific leadership in building targeting solutions that integrate effectively into existing systems and processes while delivering strong and consistent performance. Working with GC CDAO team, the Quantitative Analytics Data Scientist role provides expertise in project design, predictive model development, validation, monitoring, tracking, and implementation. To be successful in this role, you should possess the following skillsets: Python Programming. Knowledge of Artificial Intelligence and Machine Learning algorithms including NLP. SQL. Spark/PySpark. Predictive Model development. Model lifecycle and model management including monitoring, governance, and implementation. DevOps tools like Git/Bitbucket etc. Project management using JIRA. Some other highly valued skills include: DevOps tools TeamCity, Jenkins, etc. Knowledge of Financial/Banking Domain. Knowledge of GenAI tools and working. AWS. Databricks. You may be assessed on the key critical skills relevant for success in the role, such as risk and controls, change and transformation, business acumen, strategic thinking, and digital and technology, as well as job-specific technical skills. This role is based in our Noida office. Purpose of the role To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making. Accountabilities Design analytics and modeling solutions to complex business problems using domain expertise. Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments, and tools. Development of high performing, comprehensively documented analytics and modeling solutions, demonstrating their efficacy to business users and independent validation teams. Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalize them. Provision of ongoing support for the continued effectiveness of analytics and modeling solutions to users. Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy. Ensure all development activities are undertaken within the defined control environment. Assistant Vice President Expectations To advise and influence decision-making, contribute to policy development, and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions. Lead a team performing complex tasks, using well-developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviors to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviors are: L Listen and be authentic, E Energize and inspire, A Align across the enterprise, D Develop others. OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialization to complete assignments. They will identify new directions for assignments and/or projects, identifying a combination of cross-functional methodologies or practices to meet required outcomes. Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues. Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda. Take ownership for managing risk and strengthening controls in relation to the work done. Perform work that is closely related to that of other areas, which requires an understanding of how areas coordinate and contribute to the achievement of the objectives of the organization sub-function. Collaborate with other areas of work, for business-aligned support areas to keep up to speed with business activity and the business strategy. Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practices (in other areas, teams, companies, etc.) to solve problems creatively and effectively. Communicate complex information. "Complex" information could include sensitive information or information that is difficult to communicate because of its content or its audience. Influence or convince stakeholders to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset to Empower, Challenge, and Drive the operating manual for how we behave.,

As a Data Scientist AI/ML at Barclays in the Group Control Quantitative Analytics team, you will embark on a transformative journey driving innovation and excellence in our digital landscape. Your role will involve harnessing cutting-edge technology to revolutionize digital offerings, ensuring unparalleled customer experiences. Group Control Quantitative Analytics (GCQA) is a global organization of highly specialized data scientists focusing on Artificial Intelligence, Machine Learning, and Gen AI model development, governance, and monitoring. Led by Remi Cuchillo under Lee Gregory, the Chief Data and Analytics Officer (CDAO) in Group Control, GCQA is responsible for developing and managing AI/ML/GenAI models across various areas within Barclays such as Fraud, Financial Crime, Customer Due Diligence, Controls, and Security. As a Data Scientist in this position, you will provide project-specific leadership in building targeting solutions that integrate effectively into existing systems and processes while ensuring strong and consistent performance. Collaborating with the GC CDAO team, you will offer expertise in project design, predictive model development, validation, monitoring, tracking, and implementation. Key skillsets required for success in this role include Python Programming, knowledge of AI and ML algorithms including NLP, SQL, Spark/PySpark, predictive model development, model lifecycle management, DevOps tools like Git/Bitbucket, and project management using JIRA. Additional valued skills include familiarity with DevOps tools like TeamCity and Jenkins, knowledge of the Financial/Banking domain, GenAI tools, AWS, and Databricks. Your primary purpose in this role is to design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making. You will be accountable for designing analytics and modeling solutions, collaborating with technology, developing high-performing solutions, implementing models, providing ongoing support, and ensuring conformance to Barclays Enterprise Risk Management Policies. As an Analyst in this role, you are expected to perform activities in a timely manner to a high standard, drive continuous improvement, demonstrate in-depth technical knowledge and experience, lead and supervise a team if applicable, partner with other functions, take responsibility for operational processing and activities, escalate breaches appropriately, advise decision-making, manage risk, and strengthen controls. All colleagues at Barclays are expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship, as well as the Barclays Mindset of Empower, Challenge, and Drive.,

Embark on a transformative journey as a Data Scientist AI/ML at Barclays in the Group Control Quantitative Analytics team, where you'll spearhead the evolution of the digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize digital offerings, ensuring unparalleled customer experiences. Group Control Quantitative Analytics (GCQA) is a global organization of highly specialized data scientists working on Artificial Intelligence, Machine Learning, and Gen AI model development and model management, including governance and monitoring. GCQA, led by Remi Cuchillo under Lee Gregory, Chief Data and Analytics Officer (CDAO) in Group Control, is responsible for developing and managing AI/ML/GenAI models, governance, regular model monitoring, and providing analytical support across different areas within Barclays, such as Fraud, Financial Crime, Customer Due Diligence, Controls, and Security. The Data Scientist role involves project-specific leadership in building targeting solutions that integrate effectively into existing systems and processes, delivering strong and consistent performance. Collaborating with the GC CDAO team, the Quantitative Analytics Data Scientist provides expertise in project design, predictive model development, validation, monitoring, tracking, and implementation. To be successful in this role, you should possess skills in Python Programming, Artificial Intelligence, Machine Learning algorithms including NLP, SQL, Spark/PySpark, predictive model development, model lifecycle and management, DevOps tools like Git/Bitbucket, project management using JIRA, and additional skills like DevOps tools TeamCity, Jenkins, knowledge of Financial/Banking Domain, GenAI tools, AWS, and Databricks. This role is based in the Noida office and aims to design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making. Accountabilities include designing analytics and modeling solutions to complex business problems, collaborating with technology on dependencies, developing high-performing analytics solutions, implementing models, providing ongoing support, ensuring conformance to Barclays Enterprise Risk Management Policies, and working within the defined control environment. Analysts are expected to perform activities in a timely and high-standard manner, demonstrating technical knowledge and experience in their area of expertise, leading and supervising a team, partnering with other functions and business areas, and taking responsibility for risk management and strengthening controls. They are also expected to align with Barclays Values and demonstrate the Barclays Mindset. Join Barclays as a Data Scientist AI/ML and contribute to shaping the future of digital innovation within the Group Control Quantitative Analytics team.,

You have 10 to 18 years of relevant experience in Data Science. As a Data Scientist, your responsibilities will include modeling and data processing using Scala Spark/PySpark. You should have expert level knowledge of Python for data science purposes. Additionally, you will be required to work on data science concepts, model building using sklearn/PyTorch, and Graph Analytics using networkX, Neo4j, or similar graph databases. Experience in model deployment and monitoring (MLOps) is also desirable. The required skills for this Data Science position include: - Data Science - Python - Scala - Spark/PySpark - MLOps - GraphDB - Neo4j - NetworkX Our hiring process consists of the following steps: 1. Screening (HR Round) 2. Technical Round 1 3. Technical Round 2 4. Final HR Round This position is based in Pune.,