data engineer

data engineer – financial infrastructure & analytics Jobs in Bangalore

data engineer – financial infrastructure & analytics

data scientist-artificial intelligence Jobs in Bangalore

data scientist-artificial intelligence

data scientist/analyst

data scientist

<div>
 
 Maximize Your Impact with TP
 
 
 
 Welcome to TP, a global hub of innovation and empowerment, where we redefine the future. With a remarkable &euro;10 billion annual revenue and a global team of 500,000 employees serving 170 countries in over 300 languages, we lead in intelligent, digital-first solutions.
 
 
 As a globally certified Great Place to Work in 72 countries, our culture thrives on diversity, equity, and inclusion. We value your unique perspective and believe that your talent is the missing piece that completes our vision for a brighter, digitally driven tomorrow.
 
 
 
 The Opportunity
 
 
 
 TP.ai Data Services partners with the world&rsquo;s leading technology companies to design, build, and scale trustworthy AI systems. We deliver high-quality, multi-modal data solutions that fuel innovations in Generative AI, Computer Vision, NLP, RLHF, and Trust &amp; Safety. Our mission is to ensure AI systems are not only high-performing but also responsible, reliable, and ready for global scale.
 
 
 We are seeking a Data Scientist (AI/ML Ops) to take a central role in shaping how AI models are operationalized and brought to life at scale. In this role, you will design, implement, and optimize advanced data pipelines, model evaluation frameworks, and monitoring processes that ensure AI systems are trained and deployed with accuracy, efficiency, and compliance. You&rsquo;ll apply your expertise in data science and ML operationalization to create automated feedback loops, establish robust evaluation metrics, and drive continuous improvement across the AI lifecycle.
 
 
 This is a high-impact opportunity to work on frontier AI initiatives with global reach, partnering directly with leading Big Tech enterprises. You will collaborate closely with Data Engineers, AI Researchers, IT, and Product Teams to translate complex business challenges into data-driven solutions, while influencing best practices in Responsible AI and MLOps. Beyond building pipelines and models, you&rsquo;ll help define the standards for how safe, scalable, and trustworthy AI systems are delivered worldwide.
 
 
 
 The Responsibilities &amp; Duties
 
 
 
 <ul>
 <li>
 Design data preprocessing pipelines for multi-modal datasets (text, audio, video, images).
 </li>
 <li>
 Engineer features and transformations for model training, fine-tuning, and evaluation.
 </li>
 <li>
 Apply data augmentation, synthetic data generation, and bias mitigation techniques.
 </li>
 <li>
 Develop and evaluate ML models for classification, ranking, clustering, and anomaly detection tailored to operational use cases.
 </li>
 <li>
 Expertise in power analysis, significance testing, and advanced methods such as bootstrapping and Bayesian inference.
 </li>
 <li>
 Create offline/online evaluation metrics (accuracy, F1, precision/recall, latency, fairness metrics) to track model performance.
 </li>
 <li>
 Support RLHF pipelines by integrating human feedback into model optimization loops.
 </li>
 <li>
 Collaborate with engineering teams to integrate models into production pipelines.
 </li>
 <li>
 Design automated monitoring, retraining triggers, and continuous improvement loops to maintain model quality in dynamic environments.
 </li>
 <li>
 Build dashboards and reporting frameworks for real-time monitoring of model and data health.
 </li>
 <li>
 Define labeling strategies, taxonomy structures, and annotation guidelines for supervised learning.
 </li>
 <li>
 Partner with annotation platforms to ensure accuracy, throughput, and SLA compliance.
 </li>
 <li>
 Perform statistical quality checks (inter-annotator agreement, sampling-based audits).
 </li>
 <li>
 Partner with clients, product teams, and operations leads to translate business problems into data/ML solutions.
 </li>
 <li>
 Work with Legal/Privacy teams to ensure datasets meet regulatory and ethical AI standards.
 </li>
 <li>
 Contribute to internal best practices, reusable frameworks, and knowledge bases for AI/ML Operations.
 
 
 </li>
 </ul>
 
 The Qualifications
 
 
 
 <ul>
 <li>
 Master&rsquo;s or Ph.D. in Computer Science, Data Science, Applied Mathematics, or related fields.
 </li>
 <li>
 5+ years of experience in ML/AI data science with a focus on operational deployment.
 </li>
 <li>
 Track record of delivering ML models into production environments at scale.
 </li>
 <li>
 Programming: Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow), SQL.
 </li>
 <li>
 ML Techniques: Supervised/unsupervised learning, NLP, CV, RLHF.
 </li>
 <li>
 MLOps Tools: MLflow, Kubeflow, SageMaker, Vertex AI, or similar.
 </li>
 <li>
 Data Handling: Spark, Dataflow, or equivalent big data frameworks.
 </li>
 <li>
 Visualization &amp; Reporting: Tableau, Looker, or similar BI tools.
 </li>
 <li>
 Experience with Generative AI model evaluation (LLMs, diffusion models).
 </li>
 <li>
 Knowledge of Responsible AI frameworks (bias/fairness metrics, explainability).
 </li>
 <li>
 Exposure to Trust &amp; Safety operations or high-volume data environments.
 
 
 </li>
 </ul>
 
 Pre-Employment Screenings
 
 
 
 By TP policy, employment in this position will be contingent on your successful completion and passage of a comprehensive background check, including global sanctions and watch list screening.
 
 
 
 Important | Policy on Unsolicited Third-Party Candidate Submissions
 
 
 
 TP does not accept candidate submissions from unsolicited third parties, including recruiters or headhunters. Applications will not be considered, and no contractual association will be established through such submissions.
 
 
 
 Diversity, Equity &amp; Inclusion
 
 
 
 At TP, we are committed to fostering a diverse, equitable, and inclusive workplace. We welcome individuals from all backgrounds and lifestyles and do not discriminate based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or other differences.
 
 
</div>

Data Scientist

Adobe

<div>
 
 Our Company
 
 
 
 Changing the world through digital experiences is what Adobe&rsquo;s all about. We give everyone&mdash;from emerging artists to global brands&mdash;everything they need to design and deliver exceptional digital experiences! We&rsquo;re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.
 
 
 We&rsquo;re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!
 
 
 <ul>
 <li>
 com Data Scientist/Analyst &ndash; Insights, Growth, SEO, and Forecasting
 </li>
 <li>
 com Data Scientists/Analysts are a part of the A.com Digital Media (DMe - Consumer business) and Digital Experience (DX &ndash; Enterprise business) product analytics teams and operate across a broad spectrum of responsibilities such as web analytics, cross-surface data stitching/insights, hypothesis testing &amp; optimization, SEO analytics, forecasting, data modeling, and data sciences. The analysts are responsible for driving deeper customer analytics and insights using Adobe Experience Cloud (i.e., Adobe Analytics, CJA, Adobe Debugger) and Big Data Platform (Hadoop/Hive/DBx) to develop deep and meaningful insights across multiple web surfaces. As a member of the global team, you will be involved in analytics associated with various surfaces like Adobe.com, mobile, web apps, web products, and desktop apps (i.e., Creative Cloud Desktop).
 
 
 </li>
 </ul>
 
 Job Description:
 
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Location - Noida/Bangalore
 </li>
 <li>
 Experience - 3 to 5 yrs
 </li>
 <li>
 Utilize best-in-class analytics tools, including Adobe Experience Cloud (e.g., Adobe Analytics, CJA, etc.) and Hive/SQL to stitch, assess, interpret, and analyze data to deliver insights and understanding of visitor/customer behavior on key Adobe business surfaces like A.com web, mobile, web apps, desktop apps, products, checkout flows etc.
 </li>
 <li>
 Ability to draw insights from structured and unstructured data. Proactively identify and analyze trends within the data to understand visitor/customer behavior, market dynamics and surface performance using associated business performance metrics like Traffic, CVR, Product mix, High Value Actions, SEO ranking, ARR, Product engagement, LTV, CTR etc.
 </li>
 <li>
 To work with Marketing, Finance, Product, and eCommerce teams to understand end to end customer journeys on various surfaces, draw insights from the same, support RTB process, launch measurements and business targets tracking.
 </li>
 <li>
 Creation, enhancement, and application of various models used across A.com teams for Forecasting, SEO, LTV, Optimization, Next best action/product, Keyword clustering, CTR models and more.
 </li>
 <li>
 Ownership of SEO analytics including SEO data mart and various dashboards, creation, and enhancement of statistical and mathematical models for SEO and update the leadership on the evolutions in the SEO space.
 </li>
 <li>
 Ownership and sound understanding of the business, science and techniques used to set business targets for different Adobe business surfaces using various data science models and forecasting methodologies.
 </li>
 <li>
 Review test hypotheses, help develop comprehensive growth plans and success metrics along with performing quality assurance on test set ups and targeted audiences. Analyze test results and craft meaningful test summaries to provide interpretation, guidance, recommendations, and actionable insights for key business stakeholders.
 </li>
 <li>
 To understand diverse customer intent using voice of the customer analytics and to provide actionable insights for key business stakeholders.
 </li>
 <li>
 Ability to parse, stitch, and draw meaningful insights from different Adobe data sources (online, product usage, financial etc.) to better understand the cross-surface journeys across Adobe.com and Adobe products to optimize for growth and engagement KPI&rsquo;s agreed upon with products teams.
 </li>
 <li>
 Partner with data engineering team to drive creation of reports and dashboards to visually communicate insights effectively. Make complex findings easily understandable, by highlighting key takeaways and actionable recommendations.
 
 
 </li>
 </ul>
 Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.
 
 
 Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015.
</div>

Data Scientist/Analyst

<div>
 
 Introduction
 
 
 
 In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
 
 
 
 Your Role And Responsibilities
 
 
 
 <ul>
 <li>
 Scale an existing RAG code base for a production grade AI application Requirements: Proficiency in Prompt Engineering, LLMs, and Retrieval Augmented Generation Programming languages like Python or Java Experience with vector databases
 </li>
 <li>
 Experience using LLMs in software applications, including prompting, calling, and processing outputs
 </li>
 <li>
 Experience with AI frameworks such as LangChain
 </li>
 <li>
 Troubleshooting skills and creative in finding new ways to leverage LLM Experience with Azure
 </li>
 <li>
 Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations.
 
 
 </li>
 </ul>
 
 Required Technical And Professional Expertise
 
 
 
 <ul>
 <li>
 Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus.
 </li>
 <li>
 Experience and working knowledge in COBOL &amp; JAVA would be preferred
 </li>
 <li>
 Having experience in Code generation, code matching &amp; code translation Prepare the effort estimates, WBS, staffing plan, RACI, RAID etc. .
 </li>
 <li>
 Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI.
 </li>
 <li>
 Demonstrate a growth mindset to understand clients' business processes and challenges
 
 
 </li>
 </ul>
 
 Preferred Technical And Professional Experience
 
 
 
 <ul>
 <li>
 Education: Bachelor's, Master's, or Ph.D. degree in Computer Science, Artificial Intelligence, Data Science or a related field.
 </li>
 <li>
 Ability to communicate with internal and external clients to understand and define business needs, providing analytical solutions
 </li>
 <li>
 Ability to communicate results to technical and non-technical audiences
 </li>
 </ul>
</div>

Data Scientist-Artificial Intelligence

AXA XL

<div>
 
 Specialist, Data Sourcing Solutions
 
 
 
 Gurgaon/Bangalore, India
 
 
 AXA XL recognizes data and information as critical business assets, both in terms of managing risk and enabling new business opportunities. This data should not only be high quality, but also actionable - enabling AXA XL&rsquo;s executive leadership team to maximize benefits and facilitate sustained dynamic advantage. Our Innovation, Data &amp; Analytics function is focused on driving innovation through optimizing how we leverage data to drive strategy and differentiate ourselves from others. As we develop an enterprise-wide data and digital strategy that moves us toward greater focus on the use of data and data-driven insights, we are seeking a Specialist for our Data Sourcing &amp; Solutions team. The role sits across the Innovation, Data &amp; Analytics Department to ensure customer requirements are properly captured and transformed into actionable data specifications. Success in the role will require focus on proactive management of the sourcing and management of data from source through usage. At AXA XL, we view individuals holistically through their People, Business, and Technical Skills. We&rsquo;re interested in what you bring, how you think, and your potential for growth. We value diverse perspectives, recognizing that each person contributes uniquely to our team's success. We welcome candidates with relevant education and experience in a related field, as well as those with diverse educational backgrounds or equivalent experience.
 
 
 
 What You&rsquo;ll Be DOING
 
 
 
 What will your essential responsibilities include?
 
 
 <ul>
 <li>
 Data Sourcing and Vendor Collaboration: Source, evaluate, and acquire data sources that meet customer needs; collaborate with business stakeholders, third-party vendors, and source system teams to align data assets with strategic objectives.
 </li>
 <li>
 Data Integration Architecture and Documentation: Design and implement robust data integration strategies that combine datasets from internal and external sources; document data requirements for ETL processes, APIs and data pipelines to ensure traceability and maintainability.
 </li>
 <li>
 Data Modeling and Solution Development: Develop data solutions and custom data models that address specific business difficulties; translate business requirements into actionable data insights and ensure integration with existing data assets.
 </li>
 <li>
 Data Management, Security, and Accessibility: Oversee organization and governance of data within databases; implement controls to ensure data security, integrity, and timely accessibility for authorized users.
 </li>
 <li>
 Agile Delivery and Backlog Management: Work effectively within an Agile framework; define and prioritize the product backlog; collaborate with Agile teams to deliver business value and satisfy customer needs.
 </li>
 <li>
 Cross-Functional Collaboration: Collaborate with Data Engineers, Data Science, Data Management, Data Governance, Data Quality, BI Solutions, and Stakeholders to deliver end-to-end data solutions.
 </li>
 <li>
 Data Quality Assurance: Implement measures to maintain data accuracy, consistency, and completeness; perform data validation and cleansing as needed to uphold quality standards.
 </li>
 <li>
 Data Governance, Compliance, and Privacy: Adhere to data governance standards; ensure compliance with regulations and internal policies related to data usage and privacy.
 </li>
 <li>
 Technical Proficiency and Innovation: Proficient in SQL, Azure cloud technologies, and Databricks; analyze data to generate actionable insights; stay current with emerging data management technologies.
 </li>
 <li>
 Domain Expertise Development: Develop Insurance domain knowledge to improve understanding of data context and relevance to business problems.
 </li>
 <li>
 Issue Identification and Continuous Improvement: Identify data-related issues, troubleshoot problems, and recommend and implement improvements to sourcing and integration processes.
 </li>
 <li>
 Leadership, Coaching, and Knowledge Sharing: Provide guidance and mentorship to junior analysts and teammates; foster a culture of continuous learning and improvement.
 </li>
 <li>
 Stakeholder Communication and Interpretation: Translate complex technical concepts into clear, non-technical insights to drive data-informed decision-making.
 </li>
 <li>
 Innovation and Continuous Improvement: Explore innovative approaches to data acquisition, integration, and solution development to enhance efficiency and effectiveness.
 </li>
 <li>
 Data Ecosystem Stewardship: Ensure the organization&rsquo;s data ecosystem is robust, well-integrated, and capable of delivering accurate, actionable insights to support a data-driven culture.
 </li>
 <li>
 Customer-First Mindset: Prioritize service to business stakeholders and maintain a customer-first attitude in all data solutions and interactions.
 
 
 </li>
 </ul>
 You will report to Senior Scientist- Sourcing &amp; Profiling.
 
 
 
 What You Will BRING
 
 
 
 We&rsquo;re looking for someone who has these abilities and skills:
 
 
 
 Required Skills And Abilities
 
 
 
 <ul>
 <li>
 Business &amp; Insurance Acumen: Extensive data-related experience in the Insurance sector; deep expertise in data, underwriting, claims, and/or operations; able to influence, collaborate, and lead across complex, inter-related teams with competing priorities.
 </li>
 <li>
 Stakeholder Management: Manages data needs for individual projects while maintaining awareness of broader enterprise data perspectives; engages stakeholders to align on priorities and outcomes.
 </li>
 <li>
 Digital Literacy: Enthusiasm for data-driven decision-making and familiarity with modern digital/data tools and practices to support business goals.
 </li>
 <li>
 Insurance Domain Literacy: Insurance domain literacy: deep experience in data related to underwriting, claims, and/or operations; ability to influence, collaborate, and lead cross-functional teams with competing priorities.
 </li>
 <li>
 Data Culture &amp; Mindset: Data-driven culture and mindset: passion for data and experience working in a data-driven organization.
 </li>
 <li>
 Global Collaboration &amp; Delivery: Global and cross-department collaboration: experience working with team members across the globe and across departments.
 </li>
 <li>
 Innovation &amp; Continuous Improvement: Innovation and continuous improvement: ability to recommend innovations and improvements to policies, procedures, resource deployment, and core activities.
 </li>
 <li>
 Data Analytics: Robust SQL knowledge &amp; Cloud Proficiency (including data brick); ability to work with unstructured data; perform exploratory analysis; integrate internal data with external industry data to deliver holistic solutions; effectively query data sources to derive insights.
 </li>
 <li>
 Data Warehousing: Exposure to Azure cloud technologies (including Databricks) and related data storage/processing environments; capable of supporting data pipelines and data assets across the organization.
 </li>
 <li>
 Troubleshooting &amp; Debugging: (implicit in the ability to identify data-related issues and resolve data sourcing/integration problems) demonstrated through problem-solving and iterative improvement of data processes.
 </li>
 <li>
 Domain &amp; Insurance Knowledge: Insurance data analytics: extensive experience in data roles (business analyst, data analyst, analytics) within the Insurance industry and data division.
 </li>
 <li>
 Data Integration &amp; Interoperability: Data integration: ability to integrate internal data with external industry data to deliver holistic solutions.
 </li>
 <li>
 Unstructured Data Analytics: Unstructured data analytics: work with unstructured data to unlock business insights and develop data-driven insurance products.
 </li>
 <li>
 Data Quality &amp; Governance: Data quality and organization: exceptional organizational skills, attention to detail, and emphasis on data quality and governance.
 </li>
 <li>
 Project Leadership &amp; Delivery: Project ownership and resilience: capability to take ownership, work under pressure, and meet deadlines.
 
 
 </li>
 </ul>
 
 Desired Skills And Abilities
 
 
 
 <ul>
 <li>
 Customer Centricity: Demonstrates excellent presentation, communication (oral &amp; written), and relationship-building skills across all levels of management and customer interaction.
 </li>
 <li>
 Cross Functional Collaboration: Works effectively with colleagues across global teams and multiple departments; builds trust and rapport within and across groups.
 </li>
 <li>
 Analytical &amp; Strategic Mindset: Possesses effective exploratory analysis skills, high intellectual curiosity, and is an outstanding conceptual thinker who can connect dots, think critically, and assess long-term impact.
 </li>
 <li>
 Resilience &amp; Performance Excellence: Takes ownership, works under pressure, and consistently meets deadlines; demonstrates exceptional organizational skills and attention to detail.
 </li>
 <li>
 Growth Mindset &amp; Innovation: Passion for data and a habit of advocating for continuous improvement, innovation, and policy/process enhancements.
 
 
 </li>
 </ul>
 
 Who WE are
 
 
 
 AXA XL, the P&amp;C and specialty risk division of AXA, is known for solving complex risks. For mid-sized companies, multinationals and even some inspirational individuals we don&rsquo;t just provide re/insurance, we reinvent it.
 
 
 How? By combining a comprehensive and efficient capital platform, data-driven insights, leading technology, and the best talent in an agile and inclusive workspace, empowered to deliver top client service across all our lines of business &minus; property, casualty, professional, financial lines and specialty.
 
 
 With an innovative and flexible approach to risk solutions, we partner with those who move the world forward.
 
 
 Learn more at axaxl.com
 
 
 
 What we OFFER
 
 
 
 
 Inclusion
 
 
 
 AXA XL is committed to equal employment opportunity and will consider applicants regardless of gender, sexual orientation, age, ethnicity and origins, marital status, religion, disability, or any other protected characteristic. At AXA XL, we know that an inclusive culture and enables business growth and is critical to our success. That&rsquo;s why we have made a strategic commitment to attract, develop, advance and retain the most inclusive workforce possible, and create a culture where everyone can bring their full selves to work and reach their highest potential.
 
 It&rsquo;s about helping one another &mdash; and our business &mdash; to move forward and succeed.
 
 
 
 <ul>
 <li>
 Five Business Resource Groups focused on gender, LGBTQ+, ethnicity and origins, disability and inclusion with 20 Chapters around the globe.
 </li>
 <li>
 Robust support for Flexible Working Arrangements
 </li>
 <li>
 Enhanced family-friendly leave benefits
 </li>
 <li>
 Named to the Diversity Best Practices Index
 </li>
 <li>
 Signatory to the UK Women in Finance Charter
 
 
 </li>
 </ul>
 Learn more at axaxl.com/about-us/inclusion-and-diversity. AXA XL is an Equal Opportunity Employer.
 
 
 
 Total Rewards
 
 
 
 AXA XL&rsquo;s Reward program is designed to take care of what matters most to you, covering the full picture of your health, wellbeing, lifestyle and financial security. It provides competitive compensation and personalized, inclusive benefits that evolve as you do.
 
 
 We&rsquo;re committed to rewarding your contribution for the long term, so you can be your best self today and look forward to the future with confidence.
 
 
 
 Sustainability
 
 
 
 At AXA XL, Sustainability is integral to our business strategy. In an ever-changing world, AXA XL protects what matters most for our clients and communities. We know that sustainability is at the root of a more resilient future. Our 2023-26 Sustainability strategy, called &ldquo;Roots of resilience&rdquo;, focuses on protecting natural ecosystems, addressing climate change, and embedding sustainable practices across our operations.
 
 
 
 Our Pillars
 
 
 
 <ul>
 <li>
 Valuing nature: How we impact nature affects how nature impacts us. Resilient ecosystems - the foundation of a sustainable planet and society - are essential to our future. We&rsquo;re committed to protecting and restoring nature - from mangrove forests to the bees in our backyard - by increasing biodiversity awareness and inspiring clients and colleagues to put nature at the heart of their plans.
 </li>
 <li>
 Addressing climate change: The effects of a changing climate are far-reaching and significant. Unpredictable weather, increasing temperatures, and rising sea levels cause both social inequalities and environmental disruption. We're building a net zero strategy, developing insurance products and services, and mobilizing to advance thought leadership and investment in societal-led solutions.
 </li>
 <li>
 Integrating ESG: All companies have a role to play in building a more resilient future. Incorporating ESG considerations into our internal processes and practices builds resilience from the roots of our business. We&rsquo;re training our colleagues, engaging our external partners, and evolving our sustainability governance and reporting.
 </li>
 <li>
 AXA Hearts in Action: We have established volunteering and charitable giving programs to help colleagues support causes that matter most to them, known as AXA XL&rsquo;s &ldquo;Hearts in Action&rdquo; programs. These include our Matching Gifts program, Volunteering Leave, and our annual volunteering day - the Global Day of Giving.
 
 
 </li>
 </ul>
 For more information, please see axaxl.com/sustainability.
</div>

Associate Scientist, Data Sourcing & Solutions

Infosys

<div>
 Required Skills &amp; Experience
 
 
 <ul>
 <li>
 4+ years of total experience, with 3+ years in data engineering and business intelligence.
 </li>
 <li>
 4+ years of hands-on experience in Python and other open-source data engineering tools.
 </li>
 <li>
 Strong expertise in data engineering, data handling, and statistical programming using modern IT tools.
 </li>
 <li>
 Understanding of Data Warehousing, Business Intelligence, and ETL processes.
 </li>
 <li>
 Proficiency and experience with Apache Spark and Big Data technologies (e.g., Hadoop, Hive).
 </li>
 <li>
 Proven experience in Agile methodologies, including iterative development and sprint planning.
 </li>
 <li>
 Experience working in highly regulated environments, ensuring data governance and compliance.
 </li>
 <li>
 Familiarity with release governance processes and incident management tools (e.g., ServiceNow, JIRA).
 </li>
 <li>
 Exposure to cloud platforms (AWS, Azure, GCP). Key Responsibilities
 </li>
 <li>
 Lead end-to-end data engineering and reporting engagements, from requirement gathering to solution development.
 </li>
 <li>
 Design and implement scalable data pipelines, data model, and process frameworks.
 </li>
 <li>
 Collaborate with stakeholders, providing domain and technical thought.
 </li>
 <li>
 Perform Fit/Gap analysis and translate business needs into actionable data solutions.
 </li>
 <li>
 Develop interactive dashboards and reports using visualization tools or Python-based libraries.
 </li>
 <li>
 Ensure data quality, governance, and compliance across reporting solutions.
 </li>
 <li>
 Conduct performance tuning and optimization of data workflows and visualizations.
 </li>
 <li>
 Ensure compliance with release governance and manage incidents using industry-standard tools.
 </li>
 <li>
 Contribute to Unit/Organizational initiatives, including Centers of Excellence (COEs) and innovation programs.
 </li>
 </ul>
</div>

Data Engineer

Meril

<div>
 
 
 About the Role
 
 
 
 As a
 
 Quantitative Data Engineer
 
 , you will be the backbone of the data ecosystem powering our
 
 quantitative research, trading, and AI-driven strategies
 
 . You will design, build, and maintain the
 
 high-performance data infrastructure
 
 that enables low-latency, high-fidelity access to market, fundamental, and alternative data across multiple asset classes.
 
 
 This role bridges
 
 quant engineering, data systems, and research enablement
 
 , ensuring that our researchers and traders have fast, reliable, and well-documented datasets for analysis and live trading. You&rsquo;ll be part of a cross-functional team working at the intersection of
 
 finance, machine learning, and distributed systems
 
 .
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 
 Architect and maintain scalable ETL pipelines
 
 for ingesting and transforming terabytes of structured, semi-structured, and unstructured market and alternative data.
 </li>
 <li>
 
 Design time-series optimized data stores
 
 and
 
 streaming frameworks
 
 to support low-latency data access for both backtesting and live trading.
 </li>
 <li>
 
 Develop ingestion frameworks
 
 integrating vendor feeds (Bloomberg, Refinitiv, Polygon, Quandl, etc.), exchange data, and internal execution systems.
 </li>
 <li>
 
 Collaborate with quantitative researchers and ML teams
 
 to ensure data accuracy, feature availability, and schema evolution aligned with modeling needs.
 </li>
 <li>
 
 Implement data quality checks, validation pipelines, and version control mechanisms
 
 for all datasets.
 </li>
 <li>
 
 Monitor and optimize distributed compute environments
 
 (Spark, Flink, Ray, or Dask) for performance and cost efficiency.
 </li>
 <li>
 
 Automate workflows
 
 using orchestration tools (Airflow, Prefect, Dagster) for reliability and reproducibility.
 </li>
 <li>
 
 Establish best practices
 
 for metadata management, lineage tracking, and documentation.
 </li>
 <li>
 
 Contribute to internal libraries and SDKs
 
 for seamless data access by trading and research applications.
 </li>
 </ul>
 
 
 In Trading Firms, Data Engineers Typically:
 
 
 <ul>
 <li>
 Build
 
 real-time data streaming systems
 
 to capture market ticks, order books, and execution signals.
 </li>
 <li>
 Manage
 
 versioned historical data lakes
 
 for backtesting and model training.
 </li>
 <li>
 Handle
 
 multi-venue data normalization
 
 (different exchanges and instruments).
 </li>
 <li>
 Integrate
 
 alternative datasets
 
 (satellite imagery, news sentiment, ESG, supply-chain data).
 </li>
 <li>
 Work closely with
 
 quant researchers
 
 to convert raw data into
 
 research-ready features
 
 .
 </li>
 <li>
 Optimize pipelines for
 
 ultra-low latency
 
 where milliseconds can impact P&amp;L.
 </li>
 <li>
 Implement
 
 data observability frameworks
 
 to ensure uptime and quality.
 </li>
 <li>
 Collaborate with
 
 DevOps and infra engineers
 
 to scale storage, caching, and compute.
 </li>
 </ul>
 
 
 Tech Stack
 
 
 <ul>
 <li>
 
 Languages:
 
 Python, SQL, Scala, Go, Rust (optional for HFT pipelines)
 </li>
 <li>
 
 Data Processing:
 
 Apache Spark, Flink, Ray, Dask, Pandas, Polars
 </li>
 <li>
 
 Workflow Orchestration:
 
 Apache Airflow, Prefect, Dagster
 </li>
 <li>
 
 Databases &amp; Storage:
 
 PostgreSQL, ClickHouse, DuckDB, ElasticSearch, Redis
 </li>
 <li>
 
 Data Lakes:
 
 Delta Lake, Iceberg, Hudi, Parquet
 </li>
 <li>
 
 Streaming:
 
 Kafka, Redpanda, Pulsar
 </li>
 <li>
 
 Cloud &amp; Infra:
 
 AWS (S3, EMR, Lambda), GCP, Azure, Kubernetes
 </li>
 <li>
 
 Version Control &amp; Lineage:
 
 DVC, MLflow, Feast, Great Expectations
 </li>
 <li>
 
 Visualization / Monitoring:
 
 Grafana, Prometheus, Superset, DataDog
 </li>
 <li>
 
 Tools for Finance:
 
 kdb+/q (for tick data), InfluxDB, QuestDB
 </li>
 </ul>
 
 
 What You Will Gain
 
 
 <ul>
 <li>
 
 End-to-end ownership
 
 of core data infrastructure in a high-impact, mission-critical domain.
 </li>
 <li>
 Deep exposure to
 
 quantitative research workflows
 
 ,
 
 market microstructure
 
 , and
 
 real-time trading systems
 
 .
 </li>
 <li>
 
 Collaboration with elite quantitative researchers, traders, and ML scientists.
 
 </li>
 <li>
 Hands-on experience with
 
 cutting-edge distributed systems
 
 and
 
 time-series data technologies
 
 .
 </li>
 <li>
 A culture that emphasizes
 
 technical excellence, autonomy, and experimentation.
 
 </li>
 </ul>
 
 
 Qualifications
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s in
 
 Computer Science, Data Engineering, or related field.
 
 </li>
 <li>
 
 2+ years
 
 of experience building and maintaining
 
 production-grade data pipelines
 
 .
 </li>
 <li>
 Proficiency in
 
 Python
 
 ,
 
 SQL
 
 , and frameworks like
 
 Airflow
 
 ,
 
 Spark
 
 , or
 
 Flink
 
 .
 </li>
 <li>
 Familiarity with
 
 cloud storage and compute (S3, GCS, EMR, Dataproc)
 
 and
 
 versioned data lakes (Delta, Iceberg)
 
 .
 </li>
 <li>
 Experience with
 
 financial datasets
 
 ,
 
 tick-level data
 
 , or
 
 high-frequency time series
 
 is a strong plus.
 </li>
 <li>
 Strong understanding of
 
 data modeling, schema design, and performance optimization
 
 .
 </li>
 <li>
 Excellent communication skills with an ability to support
 
 multidisciplinary teams
 
 .
 </li>
 </ul>
 
 
</div>

Data Engineer – Financial Infrastructure & Analytics

Syngene International Limited

<div>
 Date: 14 Oct 2025
 
 
 Location:
 
 
 IN
 
 
 Division: Discovery Services
 
 
 
 Job Title: Junior Analytical Development Scientist - OSD
 
 
 
 
 Job Location: Bengaluru
 
 
 
 
 Department: DPA &ndash; FD
 
 
 
 
 About Syngene :
 
 Syngene (www.syngeneintl.com) is an innovation-led contract research, development and manufacturing organization offering integrated scientific services from early discovery to commercial supply.
 
 
 At Syngene, safety is at the heart of everything we do personally and professionally. Syngene has placed safety at par with business performance with shared responsibility and accountability, including following safety guidelines, procedures and SOPs, in letter and spirit
 
 
 
 Mandatory expectation for all roles as per Syngene safety guidelines
 
 
 
 <ul>
 <li>
 Overall adherence to safe practices and procedures of oneself and the teams aligned
 </li>
 <li>
 Contributing to development of procedures, practices and systems that ensures safe operations and compliance to company&rsquo;s integrity &amp; quality standards
 </li>
 <li>
 Driving a corporate culture that promotes environment, health, and safety (EHS) mindset and operational discipline at the workplace at all times.
 </li>
 <li>
 Ensuring safety of self, teams and lab/plant by adhering to safety protocols and following environment, health, and safety (EHS) requirements at all times in the workplace.
 </li>
 <li>
 Ensure all assigned mandatory trainings related to data integrity, health, and safety measures are completed on time by all members of the team including self
 </li>
 <li>
 Compliance to Syngene&rsquo; s quality standards at all times
 </li>
 <li>
 Hold self and their teams accountable for the achievement of safety goals
 </li>
 <li>
 Govern and Review safety metrics from time to time
 
 
 </li>
 </ul>
 
 Core Purpose Of The Role
 
 
 
 <ul>
 <li>
 Analytical development supporting Formulation development
 </li>
 <li>
 Routine analysis of samples
 </li>
 <li>
 Method development
 </li>
 <li>
 Instrument calibrations
 </li>
 <li>
 Documentation
 </li>
 <li>
 Report preparation
 </li>
 <li>
 Miscellaneous lab responsibilities
 
 
 </li>
 </ul>
 
 Role Accountabilities
 
 
 
 <ul>
 <li>
 Candidate should have very good educational and theoretical background.
 </li>
 <li>
 Candidate should have knowledge of calibration, method development and troubleshooting using various instruments like KF auto titrator, dissolution (I, II &amp; IV), spectroscopic instruments e.g. UV spectrometer, IR and Chromatographic instruments e.g. HPLC, GC
 </li>
 <li>
 Knowledge of various regulatory guidelines w.r.t. method development, product development and documentation
 </li>
 <li>
 Knowledge of method development for oral dosage forms w.r.t. tests like assay, degradation products, dissolutions, blend uniformity, content uniformity, cleaning method, etc.
 </li>
 <li>
 Knowledge of specification setting for oral dosage forms, in-process specifications as well as product specifications
 </li>
 <li>
 Knowledge and operating of instruments like LC-MS, GC-MS will be added advantage
 </li>
 <li>
 Good understanding of Documentation as per GxP requirements
 </li>
 <li>
 Online Lab notebook writing
 </li>
 <li>
 Method development report preparation &ndash; Assay, Degradation products, Dissolution, cleaning method, etc.
 </li>
 <li>
 Method of Analysis, Test report, SOP preparation
 </li>
 <li>
 Calibration documentation
 </li>
 <li>
 Review of documents generated by peers or juniors
 </li>
 <li>
 Should be able to search scientific literature on-line
 </li>
 <li>
 Should be a team player and able to coach juniors technically
 
 
 </li>
 </ul>
 
 Syngene Values
 
 
 
 All employees will consistently demonstrate alignment with our core values
 
 
 Excellence
 
 
 Integrity
 
 
 Professionalism
 
 
 
 Experience:
 
 More than 5 years up to 8 years
 
 
 
 Skills And Capabilities
 
 
 
 Candidate should have good proficiency for MS-office tools
 
 
 Should be able to search scientific literature on-line
 
 
 
 Behavioral Skills
 
 
 
 Strong commitment towards work, and a high level of dedication, enthusiasm, motivation, and persuasive ability in a team.
 
 
 Good speaking-listening-writing skills, attention to details, proactive self-starter.
 
 
 Ability to work successfully in a dynamic, ambiguous environment.
 
 
 Ability to meet tight deadlines and prioritize workloads.
 
 
 Ability to develop new ideas and creative solutions.
 
 
 Should be able to work in team and flexible for working in shifts.
 
 
 Should be a focused employee.
 
 
 
 Education:
 
 M.Pharm / M.Sc
 
 
 
 Equal Opportunity Employer
 
 
 
 It is the policy of Syngene to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by applicable legislation or local law. In addition, Syngene will provide reasonable accommodations for qualified individuals with disabilities.
</div>

Junior Analytical Development Scientist - OSD

Explore 52+ Data scientist in Bangalore this November. Find roles across top companies and apply now to boost your career.