2726 Data Science Jobs - Page 34

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Qualification & Experience: Minimum of 8 years of experience as a Data Scientist/Engineer with demonstrated expertise in data engineering and cloud computing technologies. Technical Responsibilities Excellent proficiency in Python, with a strong focus on developing advanced skills. Extensive exposure to NLP and image processing concepts. Proficient in version control systems like Git. In-depth understanding of Azure deployments. Expertise in OCR, ML model training, and transfer learning. Experience working with unstructured data formats such as PDFs, DOCX, and images. O Strong familiarity with data science best practices and the ML lifecycle. Strong experience with data pipeline development, ETL processes, and data engineering tools such as Apache Airflow, PySpark, or Databricks. Familiarity with cloud computing platforms like Azure, AWS, or GCP, including services like Azure Data Factory, S3, Lambda, and BigQuery. Tool Exposure: Advanced understanding and hands-on experience with Git, Azure, Python, R programming and data engineering tools such as Snowflake, Databricks, or PySpark. Data mining, cleaning and engineering: Leading the identification and merging of relevant data sources, ensuring data quality, and resolving data inconsistencies. Cloud Solutions Architecture: Designing and deploying scalable data engineering workflows on cloud platforms such as Azure, AWS, or GCP. Data Analysis : Executing complex analyses against business requirements using appropriate tools and technologies. Software Development : Leading the development of reusable, version-controlled code under minimal supervision. Big Data Processing : Developing solutions to handle large-scale data processing using tools like Hadoop, Spark, or Databricks. Principal Duties & Key Responsibilities: Leading data extraction from multiple sources, including PDFs, images, databases, and APIs. Driving optical character recognition (OCR) processes to digitize data from images. Applying advanced natural language processing (NLP) techniques to understand complex data. Developing and implementing highly accurate statistical models and data engineering pipelines to support critical business decisions and continuously monitor their performance. Designing and managing scalable cloud-based data architectures using Azure, AWS, or GCP services. Collaborating closely with business domain experts to identify and drive key business value drivers. Documenting model design choices, algorithm selection processes, and dependencies. Effectively collaborating in cross-functional teams within the CoE and across the organization. Proactively seeking opportunities to contribute beyond assigned tasks. Required Competencies: Exceptional communication and interpersonal skills. Proficiency in Microsoft Office 365 applications. Ability to work independently, demonstrate initiative, and provide strategic guidance. Strong networking, communication, and people skills. Outstanding organizational skills with the ability to work independently and as part of a team. Excellent technical writing skills. Effective problem-solving abilities. Flexibility and adaptability to work flexible hours as required. Key competencies / Values: Client Focus : Tailoring skills and understanding client needs to deliver exceptional results. Excellence : Striving for excellence defined by clients, delivering high-quality work. Trust : Building and retaining trust with clients, colleagues, and partners. Teamwork : Collaborating effectively to achieve collective success. Responsibility : Taking ownership of performance and safety, ensuring accountability.

Overview Company data team (CDO) of MSCI is responsible for the processing, maintenance, and quality control of various Issuer level data points pertaining to Fundamental data (Balance sheet, Income statement & Cashflow), Segment Data and GICS assignment to the company. These datapoints and the derived ratios based on these data in turn serve as inputs to its various products related to Equity, Fixed income and ESG & Climate of MSCI. The Quality, Process & Transformation (QPT) Team within the Company Data vertical is responsible for driving projects and efficiency initiatives across Company Data’s internal teams. It played an instrumental role in leading and shaping transformation efforts within company data by using their financial concepts , AI fundamentals , machine learning , prompt engineering , and technical skills like Python , Power BI , and SQL It is a techno-functional profile which has a perfect blend of functional knowledge of capital markets and technical expertise. As a member of this dynamic team, you will be responsible for identifying opportunities to automate and optimize manual processes, fostering a culture of continuous improvement. You will guide your peers in leveraging automation to streamline operations and deliver tangible results. If you’re passionate about AI , thrive in a fast-paced, self-driven environment, and want to leave a lasting impact on the business, this is the perfect role for you. We seek a highly skilled member with a proven track record in developing large-scale, reliable platforms from the ground up, not just applications or solutions. Experience in delivering multiple successful versions of platforms over time is a key advantage. You’ll collaborate closely with teams across product , research , operations , and program management , ensuring that the platforms you build are not only built to last but deliver immediate and long-term value. This is a highly visible and impactful role that offers the opportunity for long-term growth within MSCI . Responsibilities Your Responsibilities Take the lead in finding panic areas where processes can be improved and automated through advanced AI tools and programming solutions. Spearhead key projects aimed at upgrading outdated systems, introducing innovative methods to boost operational performance. Offer support and guidance to colleagues in utilizing tools such as Python, Power BI, SQL, and machine learning to enhance the team's technical capabilities. Partner with various teams, including product development, research, and operations, to ensure cohesive project execution and solution delivery. Contribute to the creation and implementation of reliable, scalable systems that meet both immediate needs and long-term goals. Encourage ongoing assessment of existing processes and recommend new strategies to improve operational efficiency and effectiveness. Use data analytics and visualization techniques to support informed decision-making and drive strategic initiatives. Qualifications Skills and experience that will help you excel 2-4 Years of relevant experience with solid understanding of financial principles and their application in capital markets Proficiency in AI fundamentals, prompt engineering, and machine learning techniques. Strong programming skills for automation, data analysis, and database management. Expertise in data visualization and reporting using Power BI. Solid understanding of financial principles and their application in capital markets. Experience in automating manual processes to improve efficiency. Proven track record of building scalable, reliable platforms from the ground up. Ability to guide teams in driving transformation and identifying optimization opportunities. Strong cross-functional teamwork with product, research, operations, and management teams. Skilled in identifying inefficiencies and creating innovative solutions. Ability to thrive in fast-paced, evolving environments with long-term commitment to projects. What we offer you Transparent compensation schemes and comprehensive employee benefits, tailored to your location, ensuring your financial security, health, and overall wellbeing. Flexible working arrangements, advanced technology, and collaborative workspaces. A culture of high performance and innovation where we experiment with new ideas and take responsibility for achieving results. A global network of talented colleagues, who inspire, support, and share their expertise to innovate and deliver for our clients. Global Orientation program to kickstart your journey, followed by access to our Learning@MSCI platform, LinkedIn Learning Pro and tailored learning opportunities for ongoing skills development. Multi-directional career paths that offer professional growth and development through new challenges, internal mobility and expanded roles. We actively nurture an environment that builds a sense of inclusion belonging and connection, including eight Employee Resource Groups. All Abilities, Asian Support Network, Black Leadership Network, Climate Action Network, Hola! MSCI, Pride & Allies, Women in Tech, and Women’s Leadership Forum. At MSCI we are passionate about what we do, and we are inspired by our purpose – to power better investment decisions. You’ll be part of an industry-leading network of creative, curious, and entrepreneurial pioneers. This is a space where you can challenge yourself, set new standards and perform beyond expectations for yourself, our clients, and our industry. MSCI is a leading provider of critical decision support tools and services for the global investment community. With over 50 years of expertise in research, data, and technology, we power better investment decisions by enabling clients to understand and analyze key drivers of risk and return and confidently build more effective portfolios. We create industry-leading research-enhanced solutions that clients use to gain insight into and improve transparency across the investment process. MSCI Inc. is an equal opportunity employer. It is the policy of the firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, gender, gender identity, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy (including unlawful discrimination on the basis of a legally protected parental leave), veteran status, or any other characteristic protected by law. MSCI is also committed to working with and providing reasonable accommodations to individuals with disabilities. If you are an individual with a disability and would like to request a reasonable accommodation for any part of the application process, please email Disability.Assistance@msci.com and indicate the specifics of the assistance needed. Please note, this e-mail is intended only for individuals who are requesting a reasonable workplace accommodation; it is not intended for other inquiries. To all recruitment agencies MSCI does not accept unsolicited CVs/Resumes. Please do not forward CVs/Resumes to any MSCI employee, location, or website. MSCI is not responsible for any fees related to unsolicited CVs/Resumes. Note on recruitment scams We are aware of recruitment scams where fraudsters impersonating MSCI personnel may try and elicit personal information from job seekers. Read our full note on careers.msci.com

Job Title Software and Data Science Engineer Job Summary We are seeking a highly motivated and analytical Data Scientist to join our team. The ideal candidate will possess a strong engineering background, a passion for solving technical problems, and the ability to work collaboratively with both technical and non-technical stakeholders. You will play a key role in developing and maintaining our platform, utilizing large-scale data to derive insights and drive business value, while working on both front-end and back-end components. What We Value A highly analytical approach with an eagerness to solve technical problems using data structures, storage systems, cloud infrastructure, front-end frameworks, and other technical tools. Experience or curiosity about working with large-scale data to address valuable business challenges. The ability to collaborate efficiently within teams of diverse backgrounds, including technical and non-technical individuals. Comfort in a dynamic environment with evolving objectives, with a strong focus on iteration and user feedback. What We Require A strong engineering background, preferably in Computer Science, Mathematics, Software Engineering, Physics, Data Science, or a related discipline. Proficiency in programming languages such as Python, Java, C++, TypeScript/JavaScript, or similar. Experience with both front-end and back-end development, including but not limited to Front-end development with TypeScript and JavaScript frameworks. Back-end development using Apache Spark or similar technologies. Strong problem-solving skills and the ability to think critically about complex technical issues. Strong communication skills and the ability to explain technical concepts to non-technical audiences. Responsibilities Design, build, and maintain scalable and reliable platform solutions, focusing on end-to-end data pipelines. Collaborate with cross-functional teams to identify and solve technical challenges across the stack. Utilize large-scale data to inform decision-making and enhance platform capabilities. Contribute to the development of best practices in software engineering and data management, with an emphasis on end-to-end data science workflows. Participate in code reviews and provide constructive feedback to peers. Continuously learn and stay updated on emerging technologies and industry trends.

Job Title ML Platform Engineer - AI Data Platforms ML Platform Engineering MLOps (Azure-Focused) Build and manage end-to-end ML/LLM pipelines on Azure ML using Azure DevOps for CI/CD, testing, and release automation. Operationalize LLMs and generative AI solutions (e. g. , GPT, LLaMA, Claude) with a focus on automation, security, and scalability. Develop and manage infrastructure as code using Terraform , including provisioning compute clusters (e. g. , Azure Kubernetes Service, Azure Machine Learning compute), storage, and networking. Implement robust model lifecycle management (versioning, monitoring, drift detection) with Azure-native MLOps components. Infrastructure Cloud Architecture Design highly available and performant serving environments for LLM inference using Azure Kubernetes Service (AKS) and Azure Functions or App Services . Build and manage RAG pipelines using vector databases (e. g. , Azure Cognitive Search, Redis, FAISS) and orchestrate with tools like LangChain or Semantic Kernel . Ensure security, logging, role-based access control (RBAC), and audit trails are implemented consistently across environments. Automation CI/CD Pipelines Build reusable Azure DevOps pipelines for deploying ML assets (data pre-processing, model training, evaluation, and inference services). Use Terraform to automate provisioning of Azure resources, ensuring consistent and compliant environments for data science and engineering teams. Integrate automated testing, linting, monitoring, and rollback mechanisms into the ML deployment pipeline. Collaboration Enablement Work closely with Data Scientists, Cloud Engineers, and Product Teams to deliver production-ready AI features. Contribute to solution architecture for real-time and batch AI use cases, including conversational AI, enterprise search, and summarization tools powered by LLMs. Provide technical guidance on cost optimization, scalability patterns, and high-availability ML deployments. Qualifications Skills Required Experience Bachelor s or Master s in Computer Science, Engineering, or a related field. 5+ years of experience in ML engineering, MLOps, or platform engineering roles. Strong experience deploying machine learning models on Azure using Azure ML and Azure DevOps . Proven experience managing infrastructure as code with Terraform in production environments. Technical Proficiency Proficiency in Python (PyTorch, Transformers, LangChain) and Terraform , with scripting experience in Bash or PowerShell. Experience with Docker and Kubernetes , especially within Azure (AKS). Familiarity with CI/CD principles, model registry, and ML artifact management using Azure ML and Azure DevOps Pipelines . Working knowledge of vector databases, caching strategies, and scalable inference architectures. Soft Skills Mindset Systems thinker who can design, implement, and improve robust, automated ML systems. Excellent communication and documentation skills capable of bridging platform and data science teams. Strong problem-solving mindset with a focus on delivery, reliability, and business impact. Preferred Qualifications Experience with LLMOps , prompt orchestration frameworks (LangChain, Semantic Kernel), and open-weight model deployment. Exposure to smart buildings, IoT , or edge-AI deployments. Understanding of governance, privacy, and compliance concerns in enterprise GenAI use cases. Certification in Azure (e. g. , Azure Solutions Architect, Azure AI Engineer, Terraform Associate) is a plus.

Assistant Brand Manager Social Rummy Assistant Brand Manager Social About Junglee Games With over 140 million users, Junglee Games is a leader in the online skill gaming space. Founded in San Francisco in 2012 and part of the Flutter Entertainment Group, we are revolutionizing how people play games. Our notable games include Howzat, Junglee Rummy, and Junglee Poker. Our team comprises over 1000+ talented individuals who have worked on internationally acclaimed AAA titles like Transformers and Star Wars: The Old Republic and contributed to Hollywood hits such as Avatar. Junglee s mission is to build entertainment for millions of people around the world and connect them through games. Junglee Games is not just a gaming company but a blend of innovation, data science, cutting-edge tech, and, most importantly, a values-driven culture that is creating the next set of conscious leaders. Job Overview Are you the first one in your group to jump on a trending reelCan you turn a meme into marketing magicWere looking for a trend-obsessed Assistant Social Media Manager to help us grow our brand across social platforms with scroll-stopping content that speaks to our players. This is a creative, fast-paced role where you ll play a key part in capturing attention, riding trends, and making online rummy cool, relatable, and viral . Key Responsibilities 1. Trend Spotting Creative Execution Constantly track viral trends, memes, formats, and audio especially across Instagram Reels, YouTube Shorts, and X (Twitter). Pitch and produce quick-turnaround content ideas that tie trending formats to our brand, games, and community. Work closely with designers and editors to bring those ideas to life with speed and style. 2. Content Management Help manage daily posting across all key platforms Instagram, Facebook, Twitter, YouTube, Telegram, etc. Write catchy, clever, and brand-aligned captions, hashtags, and CTAs. Maintain a consistent and playful brand tone while experimenting with new formats and angles. 3. Community Engagement Interact with followers in real time responding to comments, joining conversations, and boosting UGC. Help run contests, polls, and campaigns that encourage shares and participation. 4. Performance Monitoring Track how trend-based content is performing (reach, engagement, shares, etc. ). Share weekly insights and help refine the content strategy with learnings. Keep an eye on what competitors and creators in the gaming/RMG space are doing and do it better. Qualifications Skills Required 1-3 years of experience in social media, content, or digital marketing Obsessed with social media and pop culture. You know what s trending before it hits the mainstream. Hands-on with Reels, YouTube Shorts, and meme culture. Great copywriting chops with the ability to write fun, witty, and on-brand content. Bonus if you have basic skills in Canva, CapCut, or other quick-edit tools. Passion for gaming, cards, or digital-first brands is a huge plus! Be a part of Junglee Games to: Value Customers Data - Prioritize customers, use data-driven decisions, master KPIs, and leverage ideation and A/B testing to drive impactful outcomes. Inspire Extreme Ownership - We embrace ownership, collaborate effectively, and take pride in every detail to ensure every game becomes a smashing success. Lead with Love - We reject micromanagement and fear, fostering open dialogue, mutual growth, and a fearless yet responsible work ethic. Embrace change - Change drives progress and our strength lies in adapting swiftly and recognizing when to evolve to stay ahead. Play the Big Game - We think big, challenge norms, and innovate boldly, driving impactful results through fresh ideas and inventive problem-solving. Avail a comprehensive benefits package that includes paid gift coupons, fitness plans, gadget allowances, fuel costs, family healthcare, and much more. Know more about us Explore the world of Junglee Games through our website, www. jungleegames. com . Get a glimpse of what Life at Junglee Games looks like on LinkedIn . Here is a quick snippet of the Junglee Games Offsite 24 Liked what you saw so far Be A Junglee

Responsibilities: Develop machine learning models using Python & PyTorch. Optimize data architecture for efficiency & accuracy. Collaborate with cross-functional teams on AI projects.

We are seeking a highly detail-oriented and technically adept 3D Data Annotation Specialist to join our growing team. This role is critical in shaping high-quality datasets for training cutting-edge AI and computer vision models, particularly in domains such as LiDAR data processing, and 3D object detection. Roles and Responsibilities Qualifications: B.Tech in Computer Science, IT, or related field preferred (others may also apply strong analytical and software learning abilities required). Strong analytical and reasoning skills, with attention to spatial geometry and object relationships in 3D space. Basic understanding of 3D data formats (e.g., .LAS, .LAZ, .PLY) and visualization tools. Ability to work independently while maintaining high-quality standards. Excellent communication skills and the ability to collaborate in a fast-paced environment. Attention to detail and ability to work with precision in visual/manual tasks. Good understanding of basic geometry, coordinate systems, and file handling. Preferred Qualifications: Prior experience in 3D data annotation or LiDAR data analysis. Exposure to computer vision workflows. Comfortable working with large datasets and remote sensing data Key Responsibilities: Annotate 3D point cloud data with precision using specialized tools [ Training would be provided] Label and segment objects within LiDAR data, aerial scans, or 3D models. Follow annotation guidelines while applying logical and spatial reasoning to 3D environments. Collaborate with ML engineers and data scientists to ensure annotation accuracy and consistency. Provide feedback to improve annotation tools and workflow automation. Participate in quality control reviews and conduct re-annotation as needed

About Zscaler Serving thousands of enterprise customers around the world including 40% of Fortune 500 companies, Zscaler (NASDAQ: ZS) was founded in 2007 with a mission to make the cloud a safe place to do business and a more enjoyable experience for enterprise users. As the operator of the world’s largest security cloud, Zscaler accelerates digital transformation so enterprises can be more agile, efficient, resilient, and secure. The pioneering, AI-powered Zscaler Zero Trust Exchange™ platform, which is found in our SASE and SSE offerings, protects thousands of enterprise customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Named a Best Workplace in Technology by Fortune and others, Zscaler fosters an inclusive and supportive culture that is home to some of the brightest minds in the industry. If you thrive in an environment that is fast-paced and collaborative, and you are passionate about building and innovating for the greater good, come make your next move with Zscaler. Zscaler has an incredible story to tell, and our Marketing team is committed to sharing it in compelling and expressive ways. Our storytellers, analysts, strategists, and designers are attentive and dedicated to teaching our audience to think about cybersecurity like they never have before. You’ll collaborate with diverse, creative people around the globe to hone the Zscaler brand, increase awareness and demand, support partnerships, and drive home big wins for the world’s cloud security leader and our customers worldwide. We're looking for a Sr. Analyst, Marketing Strategy & Analytics to join our team based in Bangalore. Reporting to the Senior Manager of Marketing Analytics, you will be responsible for: Analyzing data from various sources to produce actionable marketing insights Evaluating marketing campaigns by measuring metrics like lead conversion rates, pipeline generation, ROI, and RoAS Optimizing or creating Tableau dashboards to track marketing campaign performance and inform strategies Developing regular metric reports on campaign performance with improvement hypotheses Integrating account-level insights from multiple sources including marketing automation tools, CRM systems (SFDC), and Snowflake What We're Looking for (Minimum Qualifications) Bachelor’s degree with 3-5 years in analytics, data analysis, or consulting Proficiency in aggregating, organizing, and analyzing large datasets using SQL and Snowflake Understanding of marketing technology platforms like Google Analytics, Salesforce CRM, Marketo, and Segment Experience with visualization tools like Salesforce and Tableau, focusing on design and user experience What Will Make You Stand Out (Preferred Qualifications) Hands-on experience with SFDC, Marketo, Snowflake, Python, and R 1-2 years in data science for experimental designs and hypothesis testing Experience with data pipeline tools for automating data extraction from various platforms and APIs #LI-Hybrid #LI-AM7 At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure. Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including: Various health plans Time off plans for vacation and sick time Parental leave options Retirement options Education reimbursement In-office perks, and more! By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines. Zscaler is committed to providing equal employment opportunities to all individuals. We strive to create a workplace where employees are treated with respect and have the chance to succeed. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status, or any other characteristic protected by federal, state, or local laws. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link. Pay Transparency Zscaler complies with all applicable federal, state, and local pay transparency rules. Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.

So, what’s the role all about? We are seeking a highly skilled and experienced Senior Data Scientist to join our dynamic team. The ideal candidate should have a minimum 4s of years of experience in data science, with hands-on experience in developing and implementing Generative AI solutions. The Senior Data Scientist will be responsible for developing Machine Learning models and collaborating with cross-functional teams to solve complex business problems How will you make an impact? Develop and execute advanced analytics projects from end to end, including data collection, preprocessing, model development, evaluation, and deployment. Develop predictive models and machine learning algorithms to extract actionable insights from large and complex datasets. Utilize statistical techniques and quantitative analysis to identify trends, patterns, and correlations within the data. Collaborate with stakeholders to understand business requirements and translate them into analytical solutions that drive value and impact. Stay abreast of the latest advancements in Data Science, Machine Learning, Generative AI and recommend innovative approaches to solve business challenges Have you got what it takes? Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field; advanced degree (Master's or Ph.D.) preferred. Minimum of 4 years of hands-on experience in data science and machine learning , with at least 6 months of experience in Generative AI development. Proficiency in programming languages such as Python or R, as well as experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn, Hugging Face - Transformers, LangChain etc.). Strong understanding of machine learning techniques and algorithms, including supervised and unsupervised learning, regression, classification, clustering, and deep learning. Strong understanding of LLMs, NLP techniques, and evaluation methods for generative outputs. Solid foundation in prompt engineering for optimizing AI-generated outputs across different tasks and domains. Excellent problem-solving skills and ability to work independently as well as collaboratively in a fast-paced environment. Strong communication and interpersonal skills, with the ability to effectively communicate complex technical concepts to diverse audiences. Proven leadership abilities, with experience in mentoring junior team members and leading cross-functional projects. Publications or contributions to the data science community, such as conference presentations, research papers, or open-source projects. Preferred Qualifications: Experience working in industries such as finance, banking. Familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and related services for building and deploying machine learning models. Knowledge of data visualization tools (e.g., Tableau, Power BI) for creating interactive dashboards and reports. Publications or contributions to the data science community, such as conference presentations, research papers, or open-source projects. Hands-on experience with vector databases (e.g. Pinecone) and embedding techniques. What’s in it for you? Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr! Enjoy NiCE-FLEX! At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. Requisition ID: 7409 Reporting into: Tech Manager Role Type: Individual Contributor

ROLES & RESPONSIBILITIES: Classroom Teaching and Facilitation of foundational subjects of Full-Stack Development or Data Science Entitled for the delivery and facilitation of programs like B.Tech - Full-Stack Development, BCA - Full-Stack Development Curriculum Content Creation Coordinating & conducting Workshops/Masterclasses in Full-Stack Development, Python Programming, Data Science, IOT, and the other relevant subject matter Mentoring and preparing students for Internships and Placements Adhering to Partnered University Norms of Examination, Evaluation and other Important academic administration Mentoring students for live projects, assignments, personal guidance, and counseling. Extending offline personal support to students for feedback and doubt resolution Maintaining class records and other relevant academic data Final student assessment and evaluating final scores/credit score and relevant submissions the University Liaison with Academic Head and Dean of partnered University. MUST HAVES: Committed to Mission and Values - Has a clear understanding of mission and values. Has a passion for facilitating learning and for enabling students to navigate their own learning journey Ethics and Integrity - Demonstrates integrity, ethical behavior and practices in all aspects of the role including relationships with students, colleagues and external entities Communicates effectively - Adapts oral and written communication approach and style to the audience and based on the message also listens attentively to others Responsive - Provides timely and substantive feedback. Always responsive to students unique learning paths Persuades - Conveys a point of view or argument in a way that stimulates thought and motivates the student or colleague to take action or consider an alternative Collaborative - Works cooperatively with others across the institution and beyond, including the Laureate network, the community and through partnerships. Represents own interests while being inclusive and fair to others Situational Adaptability - Recognizes and adapts to situations that call for different approaches to the facilitation of learning, influencing, relationship building and leading Being Resilient - Maintains a focused and optimistic disposition under pressure. Learns and grows from hardship experiences•Accountable - Takes personal responsibility for own goals and outcomes to ensure student success. Establishes clear expectations, follows through on commitments to students and holds them accountable for assignments and performance. Action Oriented - Takes on new opportunities and tough challenges with a sense of urgency, high energy and enthusiasm.

Artificial Intelligence and Machine Learning Engineering – Associate Director, Corporate Technology

Looking for experienced Data Scientist Candidates. Job Description Leveraging knowledge in analytical and statistical algorithms to assist stakeholders in improving their business Partnering on the design and implementation of statistical data quality procedures for existing and new data sources Communicating complex data science solutions, concepts, and analyses to team members and business leaders Presenting data insights & recommendations to key stakeholders Establishing links across existing data sources and finding new, interesting data correlations Ensuring testing and validation are components of all analytics solutions Skills : Strong proficiency in predictive analytics, prescriptive analytics, AI, machine learning, and statistical modeling Proficiency in programming languages such as Python and SQL for data analysis and model development. Working with text data including Natural Language Processing (NLP) techniques such as tokenization, lemmatization, sentiment analysis, text classification, topic modeling, and entity recognition Hands-on experience with advanced AI techniques such as Retrieval-Augmented Generation (RAG), vector databases, and LLM integration for enhanced information retrieval and generation, GPT, and BERT Strong understanding of Machine Learning concepts including supervised and unsupervised learning, model training, evaluation, and deployment

Notice Period : Immediate - 15 Days About the Role : We are seeking a highly skilled Senior Data Scientist to join our team and contribute to cutting-edge projects. As a key member of our data science team, you will leverage your expertise in machine learning, natural language processing, and data engineering to develop innovative solutions that drive business value. Responsibilities : - Machine Learning Model Development : Design, develop, and deploy advanced machine learning models, focusing on natural language processing tasks such as text classification, sentiment analysis, and language generation. - Data Engineering : Extract, transform, and load (ETL) data from various sources, ensuring data quality and consistency. - NLP Techniques : Apply state-of-the-art NLP techniques, including language models and text processing, to solve complex problems. - Python and ML Frameworks : Utilize Python programming language and popular ML frameworks like PyTorch or TensorFlow to build efficient and scalable models. - Cloud and Containerization : Leverage cloud platforms (GCP, AWS) and containerization technologies (Docker) for efficient deployment and management of ML models. - Database Management : Work with relational databases (Postgres, MySQL) to store, manage, and query large datasets. - Knowledge Graphs and ML Publications : Contribute to the development of knowledge graphs and stay updated with the latest advancements in the field through research and publications. Qualifications : Experience : 4-7 years of hands-on experience in data science, with a strong focus on machine learning and natural language processing. Technical Skills : - Proficiency in Python programming language. - Deep understanding of machine learning algorithms and techniques. - Expertise in NLP, including language models and text processing. - Familiarity with ML frameworks like PyTorch or TensorFlow. - Experience with cloud platforms (GCP, AWS) and containerization (Docker). - Knowledge of relational databases (Postgres, MySQL). Soft Skills : - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Ability to work independently and as part of a team.

Management Level: Ind & Func AI Decision Science Senior Manager Location: Gurgaon,Bangalore Must-have skills: Risk Analytics, Model Development, Validation, and Auditing, Performance Evaluation, Monitoring, Governance, Statistical Techniques:Linear Regression, Logistic Regression, GLM, GBM, XGBoost, Time Series (ARMA/ARIMA), Programming Languages:SAS, R, Python, Spark, Scala, Tools:Tableau, PowerBI, Regulatory Knowledge:Basel/CCAR/DFAST/CECL/IFRS9, Risk Reporting and Dashboard Solutions Good to have skills: Advanced Data Science Techniques, AML, Operational Risk Modelling, Cloud Platform Experience (AWS/Azure/GCP), Machine Learning Interpretability and Bias Algorithms Job Summary We are seeking a highly skilled Ind & Func AI Decision Science Consultant to join the Accenture Strategy & Consulting team in the Global Network Data & AI practice. You will be responsible for risk model development, validation, and auditing activities, ensuring performance evaluation, monitoring, governance, and documentation. This role offers opportunities to work with top financial clients globally, utilizing cutting-edge technologies to drive business capabilities and foster innovation. Roles & Responsibilities: Engagement Execution Lead client engagements that may involve model development, validation, governance, risk strategy, transformation, implementation, and end-to-end delivery of risk management solutions for Accentures clients. Advise clients on a wide range of Credit, Market, and Operational Risk and Management/Analytics initiatives. Projects may involve Risk Management advisory work for CROs, CFOs, etc., to achieve a variety of business, operational, and regulatory outcomes. Be a trusted advisor to senior executives and management on their business needs and issues. Develop and frame a Proof of Concept for key clients, where applicable, including scoping, staffing, engagement setup, and execution. Practice Enablement Mentor, groom, and counsel analysts, consultants, and managers to be successful and effective Management Consultants. Support development of the Risk Analytics Practice by driving initiatives around staffing, quality management, recruitment, capability development, knowledge management, etc. Develop thought capital and disseminate information around current and emerging trends in Financial Risk Management. Contribute to development of Accenture Points-of-View on a variety of risk analytics topics. Publish research and present ideas at industry conferences and seminars. Opportunity Development Identify business development opportunities for our Risk Management offerings in the Banking and Capital Market domains. Develop compelling business case/response to new business opportunities. Work with deal teams to provide subject matter expertise on credit, market, and operational risk-related topics and participate in development of client proposals and RFP responses. Client Relationship Development Develop trusted relationships with internal and external clients and have an eye for qualifying potential opportunities and negotiating complex deals. Build strong relationships with global Accenture Analytics and Risk Management teams, and further develop existing relationships based on mutual benefit and synergies. Professional & Technical Skills: 11-15 years of relevant Risk Analytics experience at one or more Financial Services firms or Professional Services/Risk Advisory with significant exposure to Credit Risk: Risk Ratings, Credit Risk Methodology, PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting, IFRS9/CECL Loss Forecasting across Retail and Commercial portfolios. Market Risk: Stress Testing, Liquidity Risk, Counterparty Credit Risk, PPNR/Revenue/Loss Forecasting, Pricing. Operational Risk: Fraud Risk, Collections and Recovery, Credit Policy and Limit Management, Fraud Risk, Counterparty Credit Risk. Regulatory Knowledge: Basel II/III, Solvency, FRTB, CCAR, IFRS9/CECL, etc. Strong understanding of banking products across retail and wholesale asset classes, and expertise in frameworks and methodologies used in risk analytics for banking portfolios. Expertise in risk strategy design and supporting analytics for banking portfolios. Modeling Techniques: Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time Series (ARMA/ARIMA), ML Interpretability and Bias Algorithms. Programming Languages & Tools: SAS, R, Python, Spark, Scala, Tableau, QlikView, PowerBI, SAS VA, Moodys Risk Calc, Bloomberg, Murex, QRM. Additional Information: Masters degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities. Industry Certifications:FRM, PRM, CFA preferred. Excellent Communication and Interpersonal Skills. Willingness to travel up to 40% of the time. Qualification Experience: Minimum 11-15 years of relevant Risk Analytics experience, Exposure to Financial Services firms or Professional Services/Risk Advisory Educational Qualification: Masters degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities, Industry certifications such as FRM, PRM, CFA preferred

**Key Responsibilities** People management - Lead a team of software engineers, DS, DE, MLE, in the design, development, and delivery of software solutions. Program management - Strong program leader that has run program management functions to efficiently deliver ML projects to production and manage its operations. Work with Business stakeholders & customers in the Retail Business domain to execute the product vision using the power of AI/ML. Scope out the business requirements by performing necessary data-driven statistical analysis. Set goals and, objectives using proper business metrics and constraints. Conduct exploratory analysis on large volumes of data, understand the statistical shape, and use the right visuals to drive & present the analysis. Analyse and extract relevant information from large amounts of data and derive useful insights on a big-data scale. Create labelling manuals and work with labellers to manage ground truth data and perform feature engineering as needed. Work with software engineering teams, data engineers and ML operations team (Data Labellers, Auditors) to deliver production systems with your deep learning models. Select the right model, train, validate, test, optimise neural net models and keep improving our image and text processing models. Architecturally optimize the deep learning models for efficient inference, reduce latency, improve throughput, reduce memory footprint without sacrificing model accuracy. Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. Create and enhance model monitoring system that could measure data distribution shifts, alert when model performance degrades in production. Streamline ML operations by envisioning human in the loop kind of workflows, collect necessary labels/audit information from these workflows/processes, that can feed into improved training and algorithm development process. Maintain multiple versions of the model and ensure the controlled release of models. Manage and mentor junior data scientists, providing guidance on best practices in data science methodologies and project execution. Lead cross-functional teams in the delivery of data-driven projects, ensuring alignment with business goals and timelines. Collaborate with stakeholders to define project objectives, deliverables, and timelines. **Skills required: ** MS/PhD from reputed institution with a delivery focus. 5+ years of experience in data science, with a proven track record of delivering impactful data-driven solutions. Delivered AI/ML products/features to production. Seen the complete cycle from Scoping & analysis, Data Ops, Modelling, MLOps, Post deployment analysis. Experts in Supervised and Semi-Supervised learning techniques. Hands-on in ML Frameworks - Pytorch or TensorFlow. Hands-on in Deep learning models. Developed and fine-tuned Transformer based models. ( Input output metric, Sampling technique) Deep understanding of Transformers, GNN models and its related math & internals. Exhibit high coding standards and create production quality code with maximum efficiency. Hands-on in Data analysis & Data engineering skills involving Sqls, PySpark etc. Exposure to ML & Data services on the cloud AWS, Azure, GCP Understanding internals of compute hardware - CPU, GPU, TPU is a plus. Can leverage the power of hardware accel to optimize the model execution — PyTorch Glow, cuDNN, is a plus.

As the Director of User Acquisition & Growth Marketing, you will lead the global strategy across all digital channels for a suite of social casino games. This leadership role entails owning end-to-end growth spanning paid acquisition, engagement, retention and monetization. You will be responsible for building and managing a high-performing team, overseeing large-scale budgets and delivering measurable, sustainable growth. A deep understanding of the gaming landscape, user behavior and performance marketing will be essential, along with a passion for innovation, experimentation and data-driven execution. Core Responsibilities Lead and execute the global user acquisition and growth marketing strategy aligned with business goals across international markets Drive full-funnel growth from awareness through monetization, optimizing for LTV, CAC, ROI and churn reduction Build scalable systems for experimentation including A/B testing, segmentation, personalized journeys and AI-enabled targeting and creative automation Identify and activate new growth levers such as referrals, influencer collaborations, cross-promotions, web-to-app journeys and SEO/ASO enhancements Collaborate with Product, LiveOps, Art and Marketing teams to embed growth initiatives into core gameplay and user engagement flows Oversee campaign execution across major platforms (Meta, Google UAC, ASA, DSPs) and emerging channels, continuously optimizing for KPIs like CTR and ROAS Establish a robust growth analytics framework to track cohort behavior, funnel performance, campaign incrementality and attribution Partner with analytics and engineering teams to refine tracking infrastructure and reporting (e.g., Appsflyer, Adjust) Integrate CRM and retention strategies (push, email, in-app) into the broader growth roadmap to boost user lifetime value Mentor and scale a high-performing UA and growth marketing team, instilling a culture of continuous learning, innovation and agility Maintain up-to-date knowledge of industry trends, competitive movements, regulatory changes and platform updates Manage and optimize multi-million-dollar budgets, ensuring spend efficiency and transparent reporting to executive leadership Desired Profile 12-15 years of progressive experience in product growth and digital marketing, with at least 10 years in leadership roles Proven success in scaling user growth, ideally within the gaming or entertainment sector Hands-on experience with campaign management on Meta, Google UAC and other major digital platforms Strong grasp of analytics, MMPs, attribution models, cohort analysis and marketing automation tools Strategic thinker with excellent leadership, analytical and communication skills Should have expertise in operating in a startup-like environment and building processes from the ground up Bachelor's or Masters degree in Marketing, Business, Data Science, or a related field Experience in the social casino or real-money gaming space preferred Familiarity with AI-driven UA automation tools and in-house performance marketing systems Exposure to global markets, especially the US and Tier-1 geographies

Who We Are At Kyndryl, we design, build, manage and modernize the mission-critical technology systems that the world depends on every day. So why work at Kyndryl? We are always moving forward – always pushing ourselves to go further in our efforts to build a more equitable, inclusive world for our employees, our customers and our communities. The Role As a Data Scientist at Kyndryl you are the bridge between business problems and innovative solutions, using a powerful blend of well-defined methodologies, statistics, mathematics, domain expertise, consulting, and software engineering. You'll wear many hats, and each day will present a new puzzle to solve, a new challenge to conquer. You will dive deep into the heart of our business, understanding its objectives and requirements – viewing them through the lens of business acumen, and converting this knowledge into a data problem. You’ll collect and explore data, seeking underlying patterns and initial insights that will guide the creation of hypotheses. Responsibilities: Lead the development and implementation of AI/ML, Generative AI and LLM projects, ensuring alignment with business objectives. Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals, demonstrating the potential of Generative AI applications. Engage effectively with customers, showcasing and demonstrating the relevance and impact of Generative AI applications in their businesses. Collaborate with cross-functional teams to integrate AI/ML solutions into cloud environments (Azure, GCP, AWS, etc.). In this role, you will embark on a transformative process of business understanding, data understanding, and data preparation. Utilizing statistical and mathematical modelling techniques, you'll have the opportunity to create models that defy convention – models that hold the key to solving intricate business challenges. With an acute eye for accuracy and generalization, you'll evaluate these models to ensure they not only solve business problems but do so optimally. Additionally, you're not just building and validating models – you’re deploying them as code to applications and processes, ensuring that the model(s) you've selected sustains its business value throughout its lifecycle. Your expertise doesn't stop at data; you'll become intimately familiar with our business processes and have the ability to navigate their complexities, identifying issues and crafting solutions that drive meaningful change in these domains. You will develop and apply standards and policies that protect our organization's most valuable asset – ensuring that data is secure, private, accurate, available, and, most importantly, usable. Your mastery extends to data management, migration, strategy, change management, and policy and regulation. If you're ready to embrace the power of data to transform our business and embark on an epic data adventure, then join us at Kyndryl. Together, let's redefine what's possible and unleash your potential. Your Future at Kyndryl Every position at Kyndryl offers a way forward to grow your career. We have opportunities that you won’t find anywhere else, including hands-on experience, learning opportunities, and the chance to certify in all four major platforms. Whether you want to broaden your knowledge base or narrow your scope and specialize in a specific sector, you can find your opportunity here. Who You Are You’re good at what you do and possess the required experience to prove it. However, equally as important – you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused – someone who prioritizes customer success in their work. And finally, you’re open and borderless – naturally inclusive in how you work with others. Required Technical and Professional Experience: Minimum of 5 years of experience in Data Science and Machine Learning, with expertise in NLP, Generative AI, LLMs, MLOps, optimization techniques, and AI solution architecture. Familiarity with business processes in 1-2 domains (e.g., Financial, Telecom, Retail, Manufacturing) to quickly understand requirements and develop solutions. Graduate/Postgraduate in computer science, computer engineering, or equivalent with minimum of 10 years of experience in the IT industry. Past experience in responding to or solutioning for RFPs, customer proposals, and customer presentations/orals. Strong understanding of Transformers, LLMs, Fine Tuning, Agents, and RAG techniques. Experience using LLM models on cloud platforms (Azure OpenAI, AWS Bedrock, GCP Vertex AI). Experience in AI/ML, with a focus on Generative AI and Large Language Models. Proven track record in working with major cloud platforms (Azure, GCP, AWS). Understanding of how to deploy LLMs on cloud/on-premise and use APIs to build industry solutions. Strong knowledge in programming, specifically in Python / R. Be well equipped to understand machine learning algorithms and be versatile enough to implement them in pure NumPy, TensorFlow or PyTorch as required Good understand of Mathematics Fundamentals like Statistics, Probability, Linear Algebra, and Calculus Experience in Data mining and providing data insights using visualization Knowledge in MySQL or NoSQL Databases will be added advantage Preferred Technical And Professional Experience Certification in one or more of the hyperscale's (Azure, AWS, Google Cloud Platform) Open Certified Data Scientist (Open CDS) – L2/L3 Familiarity with Agentic AI frameworks Being You Diversity is a whole lot more than what we look like or where we come from, it’s how we think and who we are. We welcome people of all cultures, backgrounds, and experiences. But we’re not doing it single-handily: Our Kyndryl Inclusion Networks are only one of many ways we create a workplace where all Kyndryls can find and provide support and advice. This dedication to welcoming everyone into our company means that Kyndryl gives you – and everyone next to you – the ability to bring your whole self to work, individually and collectively, and support the activation of our equitable culture. That’s the Kyndryl Way. What You Can Expect With state-of-the-art resources and Fortune 100 clients, every day is an opportunity to innovate, build new capabilities, new relationships, new processes, and new value. Kyndryl cares about your well-being and prides itself on offering benefits that give you choice, reflect the diversity of our employees and support you and your family through the moments that matter – wherever you are in your life journey. Our employee learning programs give you access to the best learning in the industry to receive certifications, including Microsoft, Google, Amazon, Skillsoft, and many more. Through our company-wide volunteering and giving platform, you can donate, start fundraisers, volunteer, and search over 2 million non-profit organizations. At Kyndryl, we invest heavily in you, we want you to succeed so that together, we will all succeed. Get Referred! If you know someone that works at Kyndryl, when asked ‘How Did You Hear About Us’ during the application process, select ‘Employee Referral’ and enter your contact's Kyndryl email address.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role & responsibilities Design, prepare and deliver lectures and hands-on training sessions on: Python programming Machine Learning Data Analytics Deep Learning Statistics and Probability Tools like NumPy, Pandas, Scikit-learn, Matplotlib, Jupyter, etc. Develop and update curriculum, course content, and learning materials. Conduct assessments, evaluate student performance, and provide constructive feedback. Mentor students on academic and project work. Stay current with the latest developments in the field and incorporate new tools and technologies. Conduct workshops, seminars, and guest lectures to enhance learning outcomes. Collaborate with academic and administrative teams to ensure effective course delivery. Required skills: Bachelor's/Masters degree Strong proficiency in Python and data analysis libraries. Hands-on experience with machine learning algorithms and frameworks. Good understanding of statistical techniques and data visualization. Prior teaching/training experience preferred. Excellent communication and presentation skills. Ability to simplify complex topics for beginner to advanced learners.

Job Description: Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine learning, or related discipline) • Good programming skills in Python with strong working knowledge of Pythons numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc. • Experience with LMs (Llama (1/2/3), T5, Falcon, Langchain or framework similar like Langchain) • Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning • Candidate must be comfortable interpreting research papers and architecture diagrams of Language Models • Candidate must be comfortable with LORA, RAG, Instruct fine-tuning, Quantization, etc. • Predictive modelling experience in Python (Time Series/ Multivariable/ Causal) • Experience applying various machine learning techniques and understanding the key parameters that affect their performance • Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs • Excellent verbal and written communication • Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects. Roles & Responsibilities: • Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities: • Connect with internal / external POC to understand the business requirements • Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis • Create project plan and sprints for milestones / deliverables • Spin VM, create and optimize clusters for Data Science workflows • Create data pipelines to ingest data effectively • Assure the quality of data with proactive checks and resolve the gaps • Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant ML/DL algorithms • Research whether similar solutions have been already developed before building ML models • Create optimized data models to query relevant data efficiently • Run relevant ML / DL algorithms for business goal seek • Optimize and validate these ML / DL models to scale • Create light applications, simulators, and scenario builders to help business consume the end outputs • Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively • Integrate and operationalize the models in client ecosystem • Document project artifacts and log failures and exceptions. • Measure, articulate impact of DS projects on business metrics and finetune the workflow based on feedbacks

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.