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Senior Data Scientist, SAP Enterprise Cloud ServicesWe help the world run better At SAP, we enable you to bring out your best. Our company culture is focused on collaboration and a shared passion to help the world run better. How? We focus every day on building the foundation for tomorrow and creating a workplace that embraces differences, values flexibility, and is aligned to our purpose-driven and future-focused work. We offer a highly collaborative, caring team environment with a strong focus on learning and development, recognition for your individual contributions, and a variety of benefit options for you to choose from. What you will do <ul type="disc"><li>Collect, prepare and structure data from various sources</li><li>Analyze big data volumes to gain insights, detect pattern and trends</li><li>Create and maintain notebooks for data analysis</li><li>Development and Appliance of Models in the discipline of LLM, Machine Learning and Predictive Analytics</li><li>Interpretation and Visualization of Analysis results</li><li>Derive recommendations and provide support to decisions - based on the data analysis</li><li>Continuous improvement of models and processes</li><li>Develop new methods of analysis</li></ul> What you bring <ul type="disc"><li>Bachelor’s, Master’s or Ph.D. in Engineering, Computer Science, Statistics, or related field</li><li>4-8 years of hands-on experience in data science and machine learning</li><li>Proficiency in Python</li><li>Experience in statistical modeling, predictive analytics and data mining techniques</li><li>Understanding of algorithm design, data cleaning, and feature engineering</li><li>Ability to work in fast-paced, collaborative teams on multiple concurrent projects</li><li>Analytical skills with the ability for abstract thinking, problem-solving skills and attention to detail</li><li>Good communication skills, with the ability to convey complex data insights to non-technical stakeholders </li></ul>Nice to have <ul type="disc"><li>Experience with big data technologies (e.g. Databricks)</li><li>Exposure to DevOps practic</li></ul> Meet the Team Join the Productization team, the group driving the ECS Delivery AIOps vision and strategy. We focus on AIOps end-to-end. By leveraging telemetry, automation, and machine learning to make operations smarter and more reliable. In close partnership with Data Science, we turn raw data into actionable insights and build rapid PoCs that validate and shape our AIOps roadmap. If you’re excited to transform operations with AI at scale, this is where you can make it happen.  ​Bring out your bestSAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.We win with inclusionSAP’s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better and more equitable world. SAP is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to the values of Equal Employment Opportunity and provide accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the <a href="https://one.int.sap/me@sap/jobs_at_sap#17498858-1050-415e-8d82-21f91655666b_96fc">SAP Referral Policy</a>. Specific conditions may apply for roles in Vocational Training.EOE AA M/F/Vet/Disability:Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, age, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability. Successful candidates might be required to undergo a background verification with an external vendor.Requisition ID: 432491  | Work Area: Software-Design and Development  | Expected Travel: 0 - 10%  | Career Status: Professional  | Employment Type: Regular Full Time   | Additional Locations: #LI-Hybrid.<h4>Experience Level</h4>Senior Level

Sap India Private Limited

Data Scientist

BI Developer Skills - PowerBI, ETL, SQLExperience - 2No. of Openings - 3 Share your resume now.

Dev Information Technology LTD

BI Developer

Sr.Data ScientistYou will work with diverse datasets, from structured logs to unstructured events, to build intelligent systems for event correlation, root cause analysis, predictive maintenance, and autonomous remediation, ultimately driving significant operational efficiencies and improving service availability. This position requires a blend of deep technical expertise in machine learning, a strong understanding of IT operations, and a commitment to operationalizing AI solutions at scale.As a Senior Data Scientist, your responsibilities will include, but are not limited to:<ul><li>Machine Learning Solution Development:<ul><li>Design, develop, and implement advanced machine learning models (supervised and unsupervised) to solve complex IT Operations problems, including Event Correlation, Anomaly Detection, Root Cause Analysis, Predictive Analytics, and Auto-Remediation.</li><li>Leverage structured and unstructured datasets, performing extensive feature engineering and data preprocessing to optimize model performance.</li><li>Apply strong statistical modeling, hypothesis testing, and experimental design principles to ensure rigorous model validation and reliable insights.</li></ul></li><li>AI/ML Product &amp; Platform Development:<ul><li>Lead the end-to-end development of Data Science products, from conceptualization and prototyping to deployment and maintenance.</li><li>Develop and deploy AI Agents for automating workflows in IT operations, particularly within Networks and CyberSecurity domains.</li><li>Implement RAG (Retrieval Augmented Generation) based retrieval frameworks for state-of-the-art models to enhance contextual understanding and response generation.</li><li>Adopt AI to detect and redact sensitive data in logs, and implement central data tagging for all logs to improve AI Model performance and governance.</li></ul></li><li>MLOps &amp; Deployment:<ul><li>Drive the operationalization of machine learning models through robust MLOps/LLMOps practices, ensuring scalability, reliability, and maintainability.</li><li>Implement models as a service via APIs, utilizing containerization technologies (Docker, Kubernetes) for efficient deployment and management.</li><li>Design, build, and automate resilient Data Pipelines in cloud environments (GCP/Azure) using AI Agents and relevant cloud services.</li></ul></li><li>Cloud &amp; DevOps Integration:<ul><li>Integrate data science solutions with existing IT infrastructure and AIOps platforms (e.g., IBM Cloud Paks, Moogsoft, BigPanda, Dynatrace).</li><li>Enable and optimize AIOps features within Data Analytics tools, Monitoring tools, or dedicated AIOps platforms.</li><li>Champion DevOps practices, including CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions), infrastructure-as-code (Terraform, Ansible, CloudFormation), and automation to streamline development and deployment workflows.</li></ul></li><li>Performance &amp; Reliability:<ul><li>Monitor and optimize platform performance, ensuring systems are running efficiently and meeting defined Service Level Agreements (SLAs).</li><li>Lead incident management efforts related to data science systems and implement continuous improvements to enhance reliability and resilience.</li></ul></li><li>Leadership &amp; Collaboration:<ul><li>Translate complex business problems into data science solutions, understanding their strategic implications and potential business value.</li><li>Collaborate effectively with cross-functional teams including engineering, product management, and operations to define project scope, requirements, and success metrics.</li><li>Mentor junior data scientists and engineers, fostering a culture of technical excellence, continuous learning, and innovation.</li><li>Clearly articulate complex technical concepts, findings, and recommendations to both technical and non-technical audiences, influencing decision-making and driving actionable outcomes.</li></ul></li><li>Best Practices:<ul><li>Uphold best engineering practices, including rigorous code reviews, comprehensive testing, and thorough documentation.</li><li>Maintain a strong focus on building maintainable, scalable, and secure systems.</li></ul></li></ul><ul><li>Education:<ul><li>Bachelors or Master's in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.</li></ul></li><li>Experience:<ul><li>8+ years of  IT and 5+yrs of progressive experience as a Data Scientist, with a significant focus on applying ML/AI in IT Operations, AIOps, or a related domain.</li><li>Proven track record of building and deploying machine learning models into production environments.</li><li>Demonstrated experience with MLOps/LLMOps principles and tools.</li><li>Experience with designing and implementing microservices and serverless architectures.</li><li>Hands-on experience with containerization technologies (Docker, Kubernetes).</li></ul></li><li>Technical Skills:<ul><li>Programming: Proficiency in at least one major programming language, preferably Python, sufficient to effectively communicate with and guide engineering teams. (Java is also a plus).</li><li>Machine Learning: Strong theoretical and practical understanding of various ML algorithms (e.g., classification, regression, clustering, time-series analysis, deep learning) and their application to IT operational data.</li><li>Cloud Platforms:<ul><li>Expertise with Google Cloud Platform (GCP) services is highly preferred, including Dataflow, Pub/Sub, Cloud Logging, Compute Engine, Kubernetes Engine, Cloud Functions, BigQuery, Cloud Storage, and Vertex AI.</li><li>Experience with other major cloud providers (AWS, Azure) is also valuable.</li></ul></li><li>DevOps &amp; Tools:<ul><li>Experience with CI/CD pipelines (e.g., Jenkins, GitLab CI, GitHub Actions).</li><li>Familiarity with infrastructure-as-code tools (e.g., Terraform, Ansible, CloudFormation).</li></ul></li><li>AIOps/Observability:<ul><li>Knowledge of AIOps platforms such as IBM Cloud Paks, Moogsoft, BigPanda, Dynatrace, etc.</li><li>Experience with log analytics platforms and data tagging strategies.</li></ul></li></ul></li><li>Soft Skills:<ul><li>Exceptional analytical and problem-solving skills, with a track record of tackling ambiguous and complex challenges independently.</li><li>Strong communication and presentation skills, with the ability to articulate complex technical concepts and findings to diverse audiences and influence stakeholders.</li><li>Ability to take end-to-end ownership of data science projects.</li><li>Commitment to best engineering practices, including code reviews, testing, and documentation.</li><li>A strong desire to stay current with the latest advancements in AI, ML, and cloud technologies.</li></ul></li></ul><h4>Experience Level</h4>Senior Level

Ford Motor

Big Data Developer What You’ll Do:<ul><li>Leverage Apache Iceberg: Design and implement robust big data solutions using Apache Iceberg to manage large datasets efficiently.</li><li>Collaborate for Success: Partner with cross-functional teams to enhance data architecture and drive impactful business decisions.</li><li>Data Analysis &amp; Insights: Dive into complex data sets, extracting meaningful insights that inform strategy and operations.</li><li>Optimize Data Workflows: Ensure seamless integration and high performance across data platforms while maintaining data integrity.</li></ul> What We’re Looking For:<ul><li>Big Data Expertise: Solid experience with Big Data technologies, particularly Apache Iceberg.</li><li>Programming Skills: Proficiency in Java, Scala, or Python to develop and optimize data solutions.</li><li>Analytical Thinker: Strong analytical skills with the ability to derive insights from complex datasets.</li><li>Agile Mindset: Comfortable working in a fast-paced environment and managing multiple tasks effectively.</li></ul> Why Xoriant?<ul><li>Competitive Rewards: Enjoy a comprehensive salary and benefits package that values your expertise.</li><li>Growth Opportunities: We invest in your professional development—unlock your potential with us!</li><li>Innovative Culture: Experience a collaborative environment that celebrates creativity, teamwork, and innovation.</li></ul> <ul><li>Experience: 5-9 Years</li><li>Specialization: Apache Iceberg</li></ul> Send your resume to <a rel=\"noopener noreferrer\" href=\"mailto:pranav.dillikar@xoriant.com\" target=\"_blank\">pranav.dillikar@xoriant.com</a> with the subject line \"Big Data Developer Application.\"

Xoriant

ML Lead Job Requirements:<ul><li>Lead and mentor a team of data scientists to deliver ML-driven solutions.</li><li>Develop and implement advanced analytics, ML, and predictive models.</li><li>Build solutions using Statistics, ML, Deep Learning, or Generative AI.</li><li>10+ years industry experience in Data Science/ML projects with 2+ years of team leadership experience.</li><li>Strong expertise in Machine Learning, with experience in models like SVM, Random Forest, XG Boost, forecasting, anomaly detection, etc.</li><li>Proficiency in Python, PySpark, SQL, and libraries like Scikit Learn, Pandas, Numpy, Spark.</li><li>Exposure to MLOps and cloud-based ML model deployment (Azure, AWS, GCP).</li><li>Good to have: Deep Learning, Generative AI (LLMs, prompt engineering, Vector DBs), TensorFlow, PyTorch, Keras.</li><li>Excellent leadership, communication, and problem-solving skills with a track record of delivering quality solutions.</li><li>Relevant certifications (e.g., Azure Data Scientist Associate, AWS ML Specialty) will be an added advantage.</li></ul> <ul><li>Experience - 10+ Years</li><li>Immediate Joiners Preferred</li></ul> Share your updated resume now.

Product Lead

Data & Analytics Lead<h4>Career Category</h4>Procurement<h4>Job Description</h4>Join Amgen’s Mission of Serving PatientsAt Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.What you will doLet’s do this. Let’s change the world. We are seeking an individual who thrives in ambiguity, capable of driving data and analytics initiatives with precision and purpose. You will support the implementation of strategies, systems, and processes that enable data-driven decision-making across procurement and supply chain. Reporting to the Source-to-Contract (S2C) Technology Enablement Lead, your responsibilities will include designing the analytics strategy, building pipelines, integrating platforms, enabling visualization capabilities, leveraging GenAI tools, and delivering actionable insights that inform strategic sourcing and procurement decisions.Roles &amp; ResponsibilitiesData &amp; Analytics Strategy<ul><li>Develop and implement enhancements aligned with broader S2C strategic objectives and enterprise data strategy.</li><li>Define and manage a data and analytics roadmap, prioritizing dashboards, AI/ML models, APIs, and data products.</li><li>Track value delivery through KPIs such as cycle-time reduction, supplier risk mitigation, savings enablement, and user adoption.</li></ul>Data Engineering &amp; Integration<ul><li>Build and manage pipelines into data lakes/lakehouses (e.g., Databricks/Delta), integrating ERP, CLM, SRM, and external data sources.</li><li>Code in SQL and Python for data modeling, cleansing, and transformations.</li><li>Implement robust data quality, governance, lineage, and audit controls.</li></ul>Visualization &amp; Storytelling<ul><li>Deliver executive-ready dashboards and insights using tools such as Power BI, Tableau, or Looker.</li><li>Establish visualization standards and KPIs to enable consistent decision-making.</li><li>Convert complex analyses into clear, compelling narratives for senior stakeholders.</li></ul>Advanced Analytics &amp; GenAI<ul><li>Apply GenAI tools for procurement use cases, including contract intelligence, supplier summaries, and clause analysis.</li><li>Build predictive and prescriptive models for demand forecasting, supplier risk, and cost optimization.</li><li>Leverage ML frameworks for experimentation, feature management, and human-in-the-loop governance.</li></ul>Procurement &amp; Supply Chain Domain Leadership<ul><li>Partner with category managers to translate procurement and supply chain problems into data-driven use cases.</li><li>Support savings tracking, supplier diversity, ESG reporting, and risk analysis with data insights.</li><li>Improve supplier master data accuracy, classification, and taxonomy.</li></ul>Governance &amp; Compliance<ul><li>Ensure analytics pipelines comply with SOX, GxP, GDPR, CSRD, and internal audit requirements.</li><li>Own audit documentation, lineage records, and inspection readiness.</li><li>Implement access controls, data minimization, and privacy standards.</li></ul>Stakeholder Engagement &amp; Change Management<ul><li>Act as a liaison between business and technical stakeholders to translate requirements into scalable data solutions.</li><li>Lead training, adoption, and enablement for self-service analytics capabilities.</li><li>Manage vendor relationships and ensure SLAs are met for analytics platforms.</li></ul>Team Leadership<ul><li>Mentor analysts, engineers, and BI developers on data engineering, visualization, and governance practices.</li><li>Promote best practices in agile delivery, backlog management, and predictable outcomes.</li></ul>Functional SkillsMust-Have Skills<ul><li>Data Engineering: Hands-on experience with Databricks/Delta Lakehouse, SQL, Python, PySpark, orchestration tools, and CI/CD.</li><li>Visualization &amp; Storytelling: Proficiency with Power BI/Tableau/Looker and ability to craft executive-level narratives.</li><li>GenAI &amp; Analytics: Exposure to GenAI/ML platforms and ability to apply them in procurement/supply chain contexts.</li><li>Domain Knowledge: Strong understanding of procurement and supply chain processes, supplier master data, and compliance frameworks.</li><li>Governance &amp; Compliance: Knowledge of SOX, GxP, GDPR, and audit practices.</li></ul>Good-to-Have Skills<ul><li>Technical Liaison Experience: Ability to bridge between technical and business stakeholders.</li><li>Change Management: Familiarity with training and adoption practices for analytics and digital tools.</li><li>Data Science &amp; AI: Experience with ML experimentation, feature stores, and advanced analytics techniques.</li></ul> Soft Skills<ul><li>Communication &amp; Influence: Ability to simplify complex analytics for stakeholders across procurement, finance, IT, and executive leadership.</li><li>Strategic Thinking: Ability to design scalable, future-proof data solutions.</li><li>Collaboration: Strong cross-functional team collaboration skills, including mentorship and knowledge transfer.</li><li>Adaptability: Comfort in dynamic environments with shifting priorities.</li><li>Problem Solving: Structured approach to tackling technical and business problems.</li><li>Attention to Detail: Precision in handling data quality, governance, and regulatory documentation.</li></ul>.<h4>Experience Level</h4>Senior Level

Amgen Technology Private Limited

Data Analyst

Gen AI/MLOps Engineer Role Highlights:<ul><li>Design &amp; deploy end-to-end ML pipelines with Gen AI integration</li><li>Hands-on with CI/CD, Git, Docker, Jenkins, Kubernetes, and Kafka</li><li>Build &amp; scale solutions on AWS, GCP, or Azure</li><li>Develop ML models using Python, TensorFlow, Keras, PyTorch</li><li>Work with MLOps tools (MLFlow, Kubeflow, W&amp;B, Sagemaker, Vertex AI, Airflow, Prefect, etc.)</li><li>Collaborate across teams to deliver AI at scale</li></ul> What we’re looking for:<ul><li>6+ years of experience in ML / MLOps / Gen AI</li><li>Strong experience in cloud build, deployment &amp; orchestration tools</li><li>Knowledge of statistical modeling, data mining &amp; unstructured data analytics</li><li>Ability to drive both hands-on technical delivery and architecture discussions</li></ul> Share your updated resume now.

Collabera

Automation Process Engineer

Big Data Pyspark Engineer Impetus is actively seeking skilled individuals to join our dynamic team. We currently have below job opening and would be thrilled to explore opportunities with you! Open Position: Big Data Pyspark EngineerSkills: Python, Apache Spark, Pyspark, SQL, Big Data ecosystem, CloudExperience: 4 to 7 years

Impetus Technologies India Pvt Ltd

Cloud Automation Engineer

Senior Data Governance Specialist – Alation & Data Strategy We're hiring Senior Data Governance Specialist – Alation &amp; Data Strategy. Notice Period: Immediate to 20 Days Experience Required: 10 - 15 years Key Responsibilities Lead the design, configuration, and optimization of Alation for metadata management, data cataloguing, and lineage visualization. Implement and manage Alation Marketplace, enabling effective data discovery, sharing, and stewardship. Establish and maintain end-to-end data lineage across platforms and tools. Define and enforce data governance frameworks, policies, and standards aligned with organizational data strategy. Partner with business and technology teams to ensure metadata accuracy, stewardship accountability, and compliance with data privacy regulations. Collaborate with BI / Data Engineering teams to ensure metadata integration across ETL pipelines, data lakes, and reporting platforms. Drive data literacy and adoption of Alation across functional teams through training and best practices. Provide recommendations to enhance data quality, accessibility, and reusability within the organization. Required Skills &amp; Experience 10+ years of experience in Data Management, Governance, or related roles. 3+ years of hands-on experience with Alation, including Marketplace, Lineage, and Catalog Administration. Strong understanding of metadata management, data quality frameworks, and data lifecycle management. Experience implementing or scaling enterprise data governance programs. Working knowledge of data strategy, architecture, and compliance frameworks (e.g., DAMA-DMBOK, DCAM, GDPR, CCPA). Proficiency in SQL and familiarity with data engineering or BI tools (e.g., Power BI, Tableau, Databricks, Snowflake, or Azure Data Services). Excellent stakeholder management, communication, and documentation skills. Preferred Qualifications Certification in Alation, Collibra, or Informatica Axon. Experience in financial services, insurance, or large-scale enterprise data ecosystems. Proven record of driving data culture transformation and adoption of governance tools. Interested candidates, please share your CV.

Teamware Solutions

Data Engineer

Tableau Developer We are looking for a skilled Tableau Developer to join our team. The ideal candidate will have hands-on experience in creating, maintaining, and optimizing dashboards, reports, and visualizations that enable data-driven decision-making across the organization. Key Responsibilities:<ul><li>Develop and maintain Tableau dashboards &amp; reports</li><li>Translate business needs into data visualizations</li><li>Work with SQL &amp; multiple data sources for insights</li><li>Optimize dashboards for performance &amp; usability</li><li>Collaborate with stakeholders for BI solutions</li></ul> <ul><li>Experience: 5+ Years</li><li>Notice Period: Immediate Joiners or 15 Days (Only immediate joiners &amp; candidates serving notice period)</li></ul> Share your updated resume now.

Deqode

Salesforce Data Cloud Expert Are you passionate about Salesforce Data Cloud and have hands-on experience in:<ul><li> Data Harmonization</li><li> Customer Segmentation</li><li> Writing complex SQL queries</li><li> Data Ingestion</li></ul> Must have:-<ul><li>Experience: 4-10 years</li><li>Skill: CDP, salesforce data cloud, salesforce marketing cloud</li><li>Notice: Immediate to 30 days</li></ul> Share your updated resume now.

Axtria India Pvt Ltd (Ingenious Insights)

Cloud Engineer

Data Governance (Collibra) Developer Minimum 5 years of actual hands-on/experience in using Collibra, worked on Collibra integration with PowerBI/Snowflake + Pune location + Immediate /1 month notice period Share your resume now.

Persistent Systems Ltd

Staff Data Scientist I We look for talented Data Scientists who can roll up their sleeves and have direct impact on our company metrics.&nbsp;The performance of our models and experiments are seen astonishingly quickly – the learning loop is not measured in weeks or days, but hours and minutes. We live in what might be the fastest model-learning playgrounds in the world. We have built an infrastructure that enables model deployment at both scale and speed. As data scientists, we sit alongside engineering colleagues who enable our models to deploy. Combine this with our growing variable set of hundreds of potential features (and growing!), and this is a highly fertile environment for building, experimenting, refining and achieving real impact from your models. If models fire, the bottom-line impact to our teams is immediate – you see the value of your work incredibly fast. Who Are You?<ul><li>Our scientists are expected to possess deep expertise and experience in Ad Tech, AI/ML, and Data Science, particularly at scale. Familiarity with big data processing and cloud computing will be critical to succeed in this environment.</li><li>In addition to possessing a mathematical aptitude (Statistics, Probability Theory, Algorithms, Foundations of Machine Learning), they need to be competent with data science languages and tools, such as Python or Apache Spark; which will enable them to design scalable solutions for our advertising products, implement proof-of-concept, and evaluate them offline and online. They will also need to work with other engineers to take these solutions to live production and drive real business value.</li><li>Most importantly, we look for a passion to investigate and learn about the world from data, to ask interesting and provocative questions, and be driven to put real models into production that drive real business value.</li><li>We are open to diverse academic backgrounds, providing an intent to think and problem-solve like a data scientist. Our team includes engineers, mathematicians, computer scientists, physicists, economists and social scientists – a rock-star data scientist can come from any academic field.</li></ul> Required:<ul><li>Master’s in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research or Economics, Analytics, Data Science. Or Bachelor's from a reputed College with additional experience.</li><li>7-10 years of work experience in a quantitative field, with model building and validation experience.</li><li>Ad tech related industry experience is a plus. There, you would have applied algorithms and techniques from Machine Learning, Deep Learning and Statistics or other domains in solving real world problems and understand the practical issues of using these algorithms especially on large datasets.</li><li>Comfortable with software programming and statistical platforms such as R, Python etc. including visualization tools.</li><li>Comfortable with the big data ecosystem and Apache Spark. Familiarity with Microsoft Azure, AWS, or Google Cloud/Vertex AI will be a bonus.</li><li>Comfortable collaborating with cross-functional teams.</li><li>Familiarity with challenges of the identity-less world, particularly for iOS and Android&nbsp;</li><li>Excellent technical and business communication skills and should know how to present technical ideas in a simple manner to business counterparts.</li><li>Possess a high degree of curiosity and ability to rapidly learn new areas.</li></ul>&nbsp;What will you do?<ul><li>You will be responsible for leading one or more data science efforts for inMobi DSP, a gold mine that is being explored for riches. This involves project ideation and conceptualization, solution design, measurement and solution iteration, coaching, deployment and post deployment management.</li><li>This will also include designing, development, testing of product experiments.</li><li>You are expected to be a hands-on part of the role where you will also actively analyse data, design and develop models, and solve problems with the rest of the team.</li><li>Additionally, stakeholder management is needed. It will involve being the interface with internal stakeholders such as our Product, Engineering, Data, Infrastructure, and Business teams.&nbsp;</li><li>Our team strives for thought leadership in the sector. We encourage and support all team members to write blogs, commentary and case studies published on the InMobi blog. We also support team members across our MLAI team to speak at industry conferences and represent InMobi’s work.</li><li>You will learn how to design and build models for specific business problems. Even before that, you will be responsible for identifying the problem areas where AI can be applied to best business impact. You will learn to start a model design by anchoring in the business context and end user needs. You will learn how to connect model impact with real and measurable business impact.</li><li>You will work in a multi-functional team environment. You will collaborate and benefit from the skills of a diverse group of individuals from teams such as engineering, product, business, campaign management and creative development.</li><li>You will have the opportunity to experiment with multiple algorithms. Enduring learning comes from building, launching and reviewing performance of a particular algorithm; from asking why something worked or why it did not work; from asking how to tailor techniques to fit the problem at hand. We have an environment that makes this possible at speed.</li><li>Importantly, you will learn to become creative in designing models to be successful. Model design is not one-size-fits-all. Our models need to fit our particular problems and be modified to perform. Tougher problems require layers of models, and feedback mechanisms in a dynamic environment such as ours.</li><li>We are a company that innovates and demonstrates our thought leadership to the world, whether in products, research papers or conferences – there are many opportunities for you to shine.</li></ul>

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