1530 Data Scientist Jobs - Page 8

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. A nalytical professional who uses statistical methods, machine learning, and programming skills to extract insights and knowledge from data. Their primary goal is to solve complex business problems, make predictions, and drive strategic decision-making by uncovering patterns and trends within large datasets. In this role, you will embark on a transformative process of business understanding, data understanding, and data preparation. Utilizing statistical and mathematical modeling 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. Key Responsibilities: Problem Framing: Collaborating with stakeholders to understand business problems and translate them into data-driven questions. Data Collection and Cleaning: Sourcing, collecting, and cleaning large, often messy, datasets from various sources, preparing them for analysis. Exploratory Data Analysis (EDA): Performing initial investigations on data to discover patterns, spot anomalies, test hypotheses, and check assumptions with the help of summary statistics and graphical representations. Model Development: Building, training, and validating machine learning models (e.g., regression, classification, clustering, deep learning) to predict outcomes or identify relationships. Statistical Analysis: Applying statistical tests and methodologies to draw robust conclusions from data and quantify uncertainty. Feature Engineering: Creating new variables or transforming existing ones to improve model performance and provide deeper insights. Model Deployment: Working with engineering teams to deploy models into production environments, making them operational for real-time predictions or insights. Communication and Storytelling: Presenting complex findings and recommendations clearly and concisely to both technical and non-technical audiences, often through visualizations and narratives. Monitoring and Maintenance: Tracking model performance in production and updating models as data patterns evolve or new data becomes available. 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 Expertise 8 - 10 years of experience as an Data Scientist . Programming Languages: Strong proficiency in Python and/or R, with libraries for data manipulation (e.g., Pandas, dplyr), scientific computing (e.g., NumPy), and machine learning (e.g., Scikit-learn, TensorFlow, PyTorch). Statistics and Probability: A solid understanding of statistical inference, hypothesis testing, probability distributions, and experimental design. Machine Learning: Deep knowledge of various machine learning algorithms, their underlying principles, and when to apply them. Database Querying: Proficiency in SQL for extracting and manipulating data from relational databases. Data Visualization: Ability to create compelling and informative visualizations using tools like Matplotlib, Seaborn, Plotly, or Tableau. Big Data Concepts: Familiarity with concepts and tools for handling large datasets, though often relying on Data Engineers for infrastructure. Domain Knowledge: Understanding of the specific industry or business domain to contextualize data and insights. Preferred Technical and Professional Experience Degree in a scientific discipline, such as Computer Science, Software Engineering, or Information Technology 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.

Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Hybrid (Bengaluru) Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Alphametricx) (*Note: This is a requirement for one of Uplers' client - Technology, Information and Media) What do you need for this opportunity? Must have skills required: Cision, Experience in deploying machine learning models in production environments., Experience with media monitoring, Familiarity with media intelligence tools such as Meltwater, or media analytics platforms., or similar., Social Listening, Data Scientist, NLP Technology, Information and Media is Looking for: Job Title: Senior Data Scientist Location: Bangalore Job Type: Full-time Experience Level: Senior Client is hiring for the role of Senior or Lead Data Scientist Position to drive the business growth of our Analytics COE. We are looking at the aspirant with a proven track record of solutioning & delivering NLP solutions to Fortune 500 companies. This individual will be responsible for building unique solutions and also deliver based on the set SLAs Job Summary: As a Senior Data Scientist, you will lead the development and optimization of advanced analytics tools, with a focus on media intelligence solutions. Your work will involve analyzing large data sets from various media channels, designing algorithms to track trends, and providing actionable insights. We are looking for someone with a strong background in building media analytics or intelligence tools, combined with excellent problem-solving skills and a passion for innovation. Key Responsibilities: Lead the design and development of analytics platforms and media intelligence tools, transforming large, unstructured data into meaningful insights. Develop machine learning models for trend detection, sentiment analysis, keyword extraction, and content recommendation. Work with large-scale media data from sources such as social media, news, blogs, and other online platforms. Collaborate with cross-functional teams, including data engineers, software developers, and product managers, to deliver end-to-end solutions. Implement NLP techniques to analyze and categorize media content from multiple sources. Build and optimize data pipelines for efficient data processing, storage, and retrieval. Translate business objectives into data-driven solutions and deliver actionable insights to internal teams and clients. Mentor and guide junior data scientists, providing support in developing their technical skills and career growth. Stay updated on the latest trends in data science, AI, and media intelligence to ensure the tools and platforms remain at the cutting edge. Required Skills and Qualifications: Proven experience (7+ years) as a Data Scientist, preferably in the media intelligence or analytics tool development domain. Strong expertise in machine learning, NLP, and statistical modeling. Hands-on experience with media data analysis, including sentiment analysis, keyword analysis, and audience engagement tracking. Proficiency in Python, R, and SQL. Familiarity with big data tools such as Hadoop, Spark, Redis, Apache Flink, and cloud platforms (AWS, GCP, Azure). Strong understanding of data pipelines and experience with data processing frameworks. Ability to work with large, unstructured data sets and develop models that derive actionable insights. Excellent problem-solving skills and the ability to deliver solutions in a fast-paced environment. Strong communication and presentation skills, with the ability to explain complex data insights to non-technical stakeholders. A Master's or PhD in Data Science, Computer Science, Statistics, or a related field. Preferred Skills: Experience with media monitoring, social listening, or media analytics platforms. Experience in deploying machine learning models in production environments. Familiarity with media intelligence tools such as Meltwater, Cision, or similar. Benefits: Competitive salary and bonus structure. A collaborative work environment with access to cutting-edge technologies.

What will your day look like? - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.

Job Title:GN - SC&O - S&P Data Specialist Management Level:09 - Specialist | Location:Bangalore Must have skills:Data Science KEY RESPONSIBILITIES Data Specialist work closely with the Head of Data Services and Products teams on delivering project independently, leading data analysts to carry out defined pieces of data analysis and secondary market research. Typical work streams: Client/External Supplier Interaction Liaison with various clients/suppliers and establish long-term relationship. Set expectations with customer on deliverables, negotiate on requirements, and obtain signoffs on the final deliverable. Lead data extraction efforts and guide data analysts in obtaining and analyzing it. Project Management Manage data analysts to adhere to project deadlines. Align with all internal teams to ensure buy-in from all stakeholders on the critical process pieces. Have formal weekly status review meetings with the delivery team/ CSMs/ Management as well as the customer. Understand and resolve any internal or external issues with the processed data or product effectively and efficiently. Data Management Guide data analysts and drive end to end data handling from collection to deliverable publish. Ensure that the process is fully documented and auditable. Solve day-to-day process problems as well as logical issues identify innovative approaches and solutions. Work Experience: 5+ years of project management experience on Spend Analysis/ Procurement domain experience. Academic Qualifications:Masters or Bachelors in Engineering, Mathematics, Computer Science, Business or Economics Skills Required: Strong leadership and team management skills Excellent analytical and research capabilities comfort and proficiency in handling large data analysis and secondary market research Good spoken and written (English) communication skills should be able to participate in global team calls. Excellent MS Excel skills ability to guide others in handling and structuring analysis. Excellent attention to details, high output accuracy and out-of-box thinking to bring in innovative approaches to problems/issues in data processing. Additional Skills/Experience Desired: Background in Data Management (knowledge of analytical tools like SAS, Alteryx, Qlik sense and database tools like MS Access, SQL/Oracle database) Knowledge of taxonomies like UNSPSC, NAICS, SIC, E-Class, HTS and other custom specific taxonomies Knowledge of E2E automation for the data classification/Vendor Normalization process through ETL, Scripts or KB Lookups Knowledge of the sourcing, contract management, vendor discovery assessment, vendor risk management, invoice reconciliation & leakage detection, spend miner services, P2P process, etc..Qualification Experience:5+ years Educational Qualification:Bachelors Degree

Job Description: Data Scientist (Generative AI) Job Summary Astria Digital is hiring a skilled and innovative AI/ML Engineer with 10+ years of experience for an exciting Conversational AI Bot project. This role is available in a hybrid setup (Bangalore) or can be fully remote. Were seeking someone with deep knowledge of AI/ML fundamentals, strong hands-on experience with modern NLP tech stacks, and the ability to build and deploy Small Language Models (SLMs). Youll work on creating intelligent, responsive conversational systems using frameworks like Lang Chain and deploying models on cloud platforms such as AWS or Azure. If you're passionate about cutting-edge language models and building real-world AI solutions, wed love to connect. Skills & Responsibilities Design, develop, and optimize Conversational AI Bots using advanced NLP techniques Build and fine-tune Small Language Models (SLMs) and integrate them into conversational flows Use frameworks like LangChain, LlamaIndex, or similar to develop memory-aware, context-rich dialogue systems Implement Retrieval-Augmented Generation (RAG) and embedding techniques for intelligent responses Deploy custom-trained models on AWS (e.g., SageMaker, Lambda) or Azure (e.g., AKS, ML Studio) Deep understanding of LLM architecture, transformers, and prompt engineering Proficient with libraries such as Hugging Face Transformers, PyTorch, TensorFlow Familiarity with vector databases (e.g., FAISS, Pinecone) and chat memory stores Strong foundation in machine learning fundamentals, optimization, and evaluation techniques Collaborate with product and engineering teams to integrate AI into scalable applications Experience with MLOps, model monitoring, and continuous improvement of conversational performance Keep up with the latest advancements in Conversational AI, open-source LLMs, and fine-tuning method

Role: Data Scientist 2 Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference

Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference

We are the global technology company behind the world s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless . We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. Our team within Mastercard: The Data & Services team is a key differentiator for Mastercard, providing the cutting-edge services that are used by some of the world's largest organizations to make multi-million dollar decisions and grow their businesses. Focused on thinking big and scaling fast around the globe, this agile team is responsible for end-to-end solutions for a diverse global customer base. Centered on data-driven technologies and innovation, these services include payments-focused consulting, loyalty and marketing programs, business Test & Learn experimentation, and data-driven information and risk management services. The New Product Engineering team within Data and Services is engineering the transformation of new ideas into software solutions to test in the market, and then growing and scaling products to meet long-term demand and needs. We achieve this with a "move fast, learn fast" mindset, relentless focus on customer excellence, and a culture of collaboration and empowerment. Our solutions are instrumental in positioning Mastercard as a data & services market leader. Role and Summary Data Scientist The Data Scientist in Data & Services New Product Engineering team is responsible for creating data & analytics solutions including deep learning Artificial Intelligence (A.I.) and Machine Learning (M.L.) models that sit atop large datasets of business and finance operations gathered by mid to large companies. The Data Scientist is responsible for developing full life cycle modeling processes of data analysis, feature engineering, model training, testing, serving and monitoring. As a Data Scientist, you will: Work closely with the business owners to understand business requirements, performance metrics regarding data quality and model performance of customer facing products Work with multiple disparate sources of data, storage systems, and building processes and pipelines to provide cohesive datasets for analysis and modeling Generate and maintain and optimize data pipelines for model building and model performance evaluation Develop, test, and evaluate modern machine learning and A.I. models Oversee implementation of models Evaluate production models based on business metrics to drive continuous improvement Essential Skills: Data engineering and data science experience Experience with SQL language and one or multiple of the following database technologies: PostgreSQL, Hadoop, Spark. Good knowledge of Linux / Bash environment Python and one of the following machine learning libraries oSpark ML oTensorFlow oScikit Learn oXGBoost Good communication skills Highly skilled problem solver Exhibits a high degree of initiative At least an undergraduate degree in CS, or a STEM related field. Nice to have: Bachelor s or Master s in CS, Data Science, ML/AI, or a related STEM field Understands and implements methods to evaluate own work and others for bias, inaccuracy, and error Databricks Loves working with error-prone, messy, disparate, unstructured data Experience in working with Cloud (e.g., Azure, AWS) Experience participating in complex engineering projects in an Agile setting e.g. Scrum Mastercard is an equal opportunity employer that values diversity and inclusion. Applicants will be considered and treated without regard to gender, gender identity, race, color, ethnicity, national origin, religion, sexual orientation, veteran or disabled status, or any other characteristic protected by applicable law.

Key Responsibilities Develop and deploy personalised pricing models using historical behaviour, purchase intent, segmentation, and contextual data. Apply advanced statistical and machine learning techniques to estimate demand curves and user-level price sensitivity. Design and execute pricing A/B tests, analyzing lift, revenue impact, and user experience trade-offs. Develop dynamic pricing frameworks that adjust in real-time based on inputs such as location, time, inventory, and user cohorts. Collaborate with engineering teams to integrate models into pricing engines and user-facing platforms. Communicate findings clearly to business stakeholders and make data-backed pricing recommendations. Must-Have Qualifications 36 years of experience in data science, pricing, or quantitative strategy roles. Strong programming skills in Python and SQL; experience with libraries like scikit-learn, stats models, or XGBoost. Deep knowledge of pricing analytics, revenue management, and behavioral economics. Experience in building predictive models for conversion, elasticity, or revenue uplift. Ability to synthesize complex data into actionable strategies with business impact. Strong experimentation mindset with familiarity in causal inference and A/B testing methodologies.

We are looking for a highly motivated and skilled Data Scientist with 5 years of experience. The ideal candidate should be proficient in Python, ML frameworks, and statistical modeling. You will develop machine learning models, analyze large structured and unstructured datasets, and provide actionable insights to drive business decisions. The role requires strong analytical thinking, effective communication, and hands-on experience with modern data science tools and libraries. You'll work closely with cross-functional teams, enabling data-driven strategies that impact core business outcomes.

JOb Responsibilities: The Data Scientists will leverage expertise in advanced statistical and modelling techniques to design, prototype, and build the next-generation analytics engines and services. They will work closely with the analytics teams and business teams to derive actionable insights, helping the organization in achieving its’ strategic goals. Their work will involve high levels of interaction with the integrated analytics team, including data engineers, translators, and more senior data scientists. Has expertise in implementing complex statistical analyses for data processing, exploration, model building and implementation Lead teams of 2-3 associate data scientists in the use case building and delivery process Can communicate complex technical concepts to both technical and non-technical audience Plays a key role in driving ideation around the modelling process and developing models. Can conceptualize and drive re-iteration and fine tuning of models Contribute to knowledge building and sharing by researching best practices, documenting solutions, and continuously iterating on new ways to solve problems. Mentors junior team members to do the same REQUIRED EDUCATION AND EXPERIENCE: Master’s degree in Computer Science, Statistics, Math, Operations Research, Economics, or a related field Advanced level programming skills in at least 1 coding language (R/Python/Scala) Practical experience of developing advanced statistical and machine learning models At least 2 years of relevant analytics experience Experience in using large database systems preferred Has developed niche expertise in at least one functional domain REQUIRED SKILLS: Ability to work well in agile environments in diverse teams with multiple stakeholders Experience of leading small teams Able to problem solve complex problems and break them down into simpler parts Ability to effectively communicate complex analytical and technical content High energy and passionate individual who can work closely with other team members Strong entrepreneurial drive to test new out of the box techniques Able to prioritize workstreams and adopt an agile approach Willing to adopt an iterative approach; experimental mindset to drive innovation LOCATION: Bangalore What’s in it for you ? Disruptive projects : Work on ‘ breakthrough’ digital-and-analytics projects to enable UPL’s vision of building a future ready organization. It involves deploy ing solutions to help us increase our sales, sustain our profitability, improve our speed to market, supercharge our R&D efforts, and support the way we work internally. Help us ensure we have access to the best business insights that our data analysis can offer us. Cross functional leadership exposure : Work directly under guidance of functional leadership at UPL, on the most critical business problems for the organization (and the industry) today. It will give you exposure to a large cross-functional team (e.g.: spanning manufacturing, procurement, commercial, quality, IT/OT experts), allowing multi-functional learning in D&A deployment Environment fostering professional and personal development : Strengthen professional learning in a highly impact-oriented and meritocratic environment that is focused on delivering disproportionate business value through innovative solutions. It will be supported by on-the-job coaching from experienced domain experts, and continuous feedback from a highly motivated and capable set of peers. Comprehensive training programs for continuous development through UPL's D&A academy will help in accelerating growth opportunities. Come join us in this transformational journey! Let’s collectively Change the game with Digital & Analytics!

Shift: (GMT+05:30) Asia/Kolkata (IST) What do you need for this opportunity? Must have skills required: Machine Learning, NumPy, Data Cleaning, Python, Model evaluation, pandas, Statistics We are seeking a talented Data Scientist II to join our team. The ideal candidate will have 2-5 years of experience in data science and possess expertise in machine learning, deep learning, Python programming, SQL, Amazon Redshift, NLP, and AWS Cloud. ** Duties and Responsibilities: Develop and implement machine learning models to extract insights from large datasets. Utilize deep learning techniques to enhance data analysis and predictive modeling. Write efficient Python code to manipulate and analyze data. - Work with SQL databases to extract and transform data for analysis. Utilize Amazon Redshift for data warehousing and analytics. Apply NLP techniques to extract valuable information from unstructured data. - Utilize AWS Cloud services for data storage, processing, and analysis. Qualifications and Requirements: Bachelor's degree in Computer Science, Statistics, Mathematics, or related field. - 3-5 years of experience in data science or related field. Proficiency in machine learning, deep learning, Python programming, SQL, Amazon Redshift, NLP, and AWS Cloud. Strong analytical and problem-solving skills. - Excellent communication and teamwork abilities. * *Key Competencies - Strong analytical skills. - Problem-solving abilities. - Proficiency in machine learning and deep learning techniques. Excellent programming skills in Python. - Knowledge of SQL and database management. - Familiarity with Amazon Redshift, NLP, and AWS Cloud services. ** Performance Expectations: Develop and deploy advanced machine learning models. Extract valuable insights from complex datasets. Collaborate with cross-functional teams to drive data-driven decision-making. Stay updated on the latest trends and technologies in data science. We are looking for a motivated and skilled Data Scientist I to join our team and contribute to our data-driven initiatives. If you meet the qualifications and are passionate about data science, we encourage you to apply.

About the Role Love deep data? Love discussing solutions instead of problems? Then you could be our next Data Scientist. In a nutshell, your primary responsibility will be enhancing the productivity and utilization of the generated data. Other things you will do are: Work closely with the business stakeholders Transform scattered pieces of information into valuable data Share and present your valuable insights with peers What You Will Do Develop models and run experiments to infer insights from hard data Improve our product usability and identify new growth opportunities Understand reseller preferences to provide them with the most relevant products Designing discount programs to help our resellers sell more Help resellers better recognize end-customer preferences to improve their revenue Use data to identify bottlenecks that will help our suppliers meet their SLA requirements Model seasonal demand to predict key organizational metrics Mentor junior data scientists in the team What You Will Need Bachelor's/Master's degree in computer science (or similar degrees) 2-4 years of experience as a Data Scientist in a fast-paced organization, preferably B2C Familiarity with Neural Networks, Machine Learning, etc. Familiarity with tools like SQL, R, Python, etc. Strong understanding of Statistics and Linear Algebra Strong understanding of hypothesis/model testing and ability to identify common model testing errors Experience designing and running A/B tests and drawing insights from them Proficiency in machine learning algorithms Excellent analytical skills to fetch data from reliable sources to generate accurate insights Experience in tech and product teams is a plus Bonus points for: Experience in working on personalization or other ML problems Familiarity with Big Data tech stacks like Apache Spark, Hadoop, Redshift, etc.

JOb Responsibilities: The Data Scientists will leverage expertise in advanced statistical and modelling techniques to design, prototype, and build the next-generation analytics engines and services. They will work closely with the analytics teams and business teams to derive actionable insights, helping the organization in achieving its’ strategic goals. Their work will involve high levels of interaction with the integrated analytics team, including data engineers, translators, and more senior data scientists. Has expertise in implementing complex statistical analyses for data processing, exploration, model building and implementation Lead teams of 2-3 associate data scientists in the use case building and delivery process Can communicate complex technical concepts to both technical and non-technical audience Plays a key role in driving ideation around the modelling process and developing models. Can conceptualize and drive re-iteration and fine tuning of models Contribute to knowledge building and sharing by researching best practices, documenting solutions, and continuously iterating on new ways to solve problems. Mentors junior team members to do the same REQUIRED EDUCATION AND EXPERIENCE: Master’s degree in Computer Science, Statistics, Math, Operations Research, Economics, or a related field Advanced level programming skills in at least 1 coding language (R/Python/Scala) Practical experience of developing advanced statistical and machine learning models At least 2 years of relevant analytics experience Experience in using large database systems preferred Has developed niche expertise in at least one functional domain REQUIRED SKILLS: Ability to work well in agile environments in diverse teams with multiple stakeholders Experience of leading small teams Able to problem solve complex problems and break them down into simpler parts Ability to effectively communicate complex analytical and technical content High energy and passionate individual who can work closely with other team members Strong entrepreneurial drive to test new out of the box techniques Able to prioritize workstreams and adopt an agile approach Willing to adopt an iterative approach; experimental mindset to drive innovation

Job Title: Senior Data Scientist Intelligent Offer Management Location: Bangalore (3 days work from office) Type: Full-time(On-Site) Experience Level: 3–6 years About the Role: We are hiring a Data Scientist to lead and scale our Intelligent Offer Management engine – a key pillar of our revenue optimisation strategy. This role sits at the intersection of data science, pricing strategy, product thinking, and experimentation, enabling personalised, dynamic, and contextual offer decisions at scale. You'll work closely with product managers, business teams, and engineers to build models that recommend the right offer to the right customer at the right time. Key Responsibilities -Design and implement real-time offer recommendation models using historical purchase, engagement, and behavioural data. - Develop algorithms for dynamic pricing, offer personalisation, segmentation, and discount optimisation. - Collaborate with cross-functional stakeholders to translate business requirements into data science solutions. - Conduct A/B and multivariate experiments to evaluate offer performance and optimise offer strategies. - Build predictive models for conversion propensity, elasticity curves, and uplift measurement. - Package models for production deployment, ensuring scalability, performance, and monitoring. - Influence product design and customer journeys with data-driven insights. Must-Have Qualifications: - 3-6 years of experience in data science, quantitative analytics, or pricing strategy roles. - Proficiency in Python and SQL, with experience in building, validating, and deploying ML models. - Deep understanding of offer science, pricing elasticity, behavioural economics, and incentive systems. - Strong business acumen with the ability to balance accuracy with impact and speed. - Experience working with experimentation frameworks and statistical inference. - Ability to communicate complex insights effectively to both technical and non-technical stakeholders.

Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference.

Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/ Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference.

Role: Data Scientist 2 Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 4- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 5- Have worked across end to end in model design, development, validation, documentation & deployment. 6- Create great data stories with expertise in robust EDA and statistical inference

Role Synopsis This role is a senior-level position within a data science team, responsible for providing leadership, strategic direction, and technical expertise in the field of data science and machine learning. This role involves leading all aspects of and guiding a team of data scientists while collaborating closely with multi functional departments, such as engineering, product management, and business collaborators. The Lead Data Scientist plays a pivotal role in crafting data-driven strategies and solutions that chip in to the organization's success and growth Key Accountabilities Data Analysis and Modeling: Lead data scientists must have a confirmed foundation in data analysis and a deep understanding of various machine learning algorithms They should be able to apply these techniques to address sophisticated problems and extract valuable insights from data Out of Code computing: Use libraries that support out-of-core computing, such as Dask in Python These libraries can process data that doesn't fit into memory by reading it in smaller portions from disk Business Insight: Understanding the FDO's business objectives and aligning data initiatives with them Project Management: Being skilled in project management methodologies helps in planning and driving data science projects efficiently Machine Learning: Innovation and Strategy - Advanced Machine Learning Skills for complex models. Evaluation Collaboration and Communication: Effective communication with collaborators, Explain the modeling approach and results. Implement to privacy guidelines and recommendation with conscious balance Continuous Learning: Staying up-to-date in competitive edge. Apply methodologies to practical business challenges. Meeting with domain GPO's Data cleaning and preprocessing, analysis: The ability to clean and preprocess data effectively is a fundamental skill in any data science role Data Ethics and Privacy: Open communication with customer. Ethical considerations in algorithm design. Secure data handling, Data minimization Database Management: Proficient in database systems and SQL is required for data retrieval and storage Domain knowledge: Expertise in the domain they are working in to understand the context and requirements of the data projects better Statistical Analysis and Mathematics: Solid grasp of statistical methods and mathematical concepts is needed for data analysis, modeling, and drawing substantial insights from data Experience and Job Requirements Data Science Team plays a crucial role in driving data-informed decision-making and generating actionable insights to support the company's goals. This team is responsible for processing, analyzing, and interpreting large and complex datasets from multiple datasets to provide valuable insights and recommendations across various domains. Through advanced analytical techniques and machine learning models, the data science team helps optimize processes, predict trends, and build data-driven strategies. A bachelor's or equivalent experience or master's degree in quantitative, qualitative field such as Computer Science, Statistics, Mathematics, Physics, Engineering, or a related data field is often required Skills: Leadership role in Data Analysis, Programming proficiency in Python, SQL, Azure Databricks, Statistics & Mathematics. Leadership qualities to steer the team. Strategic direction and technical expertise Soft skills: Active listening, Translate business problems into data questions, Communication and collaboration, Presentation, Problem solving, Multi-functional, Team management, Partner management Data Sources: SAP, Concur, Salesforce, Workday, Excel files Other: Project management. Domain knowledge [Procurement, Finance, Customer], Business Insight, Critical thinking, Story telling Able to prepare analytical reports, presentations and/or visualisation dashboards to communicate findings, important metrics and insights to both technical and non-technical customers Stay up to date with industry trends, standard methodologies and new technologies in data analytics, machine learning, data science techniques.

Job Summary We are looking for an experienced Data Scientist with 3 to 5 years of hands-on experience in building and deploying machine learning and natural language processing (NLP) models. The ideal candidate should have a solid foundation in AI, strong problem-solving abilities, and a passion for applying ML/NLP techniques to solve real-world challenges. Experience in designing AI agents or working with LLMs is a strong advantage. Key Responsibilities Develop, train, and deploy machine learning and NLP models to support business and product goals. Conduct end-to-end model lifecycle management, including feature engineering, model selection, evaluation, and optimization. Perform exploratory data analysis (EDA), hypothesis testing, and derive actionable insights. Design and build AI agents and workflows that interact with LLMs and integrate into larger systems. Collaborate with cross-functional teams including product, engineering, and design to deliver AI-driven solutions. Stay updated with advancements in GenAI, LLMs, and emerging trends in the AI ecosystem. Required Qualifications Bachelors or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. 3–5 years of experience in applied machine learning, NLP, or AI model development. Proficiency in Python and commonly used data science libraries (e.g., Pandas, NumPy, Scikit-learn, Transformers). Hands-on experience with NLP frameworks (e.g., Hugging Face, spaCy) and model fine-tuning. Strong understanding of supervised/unsupervised learning, vectorization techniques, and evaluation metrics. Excellent problem-solving, communication, and collaboration skills. Preferred Qualifications Experience working with large language models (LLMs) and vector databases. Exposure to building AI agents, autonomous workflows, or prompt engineering. Familiarity with cloud platforms (e.g., AWS) and scalable ML infrastructure. Understanding of MLOps practices for model deployment and monitoring.

Working knowledge of Azure AI Working knowledge of LLM , RAG- Data insights , Reasoning Agent , Chain of thought Knowledge of Graph DB , COSMOS DB , Neo4j Prompt engineering API building Domain knowledge in Finance , data management Should have worked on enterprise AI use cases and one go live solution.

Data Scientist 2-Digital Banking Kotak 811-Regional Sales Role: Data Scientist 2 Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 4- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 5- Have worked across end to end in model design, development, validation, documentation & deployment. 6- Create great data stories with expertise in robust EDA and statistical inference

Join our Team About This Opportunity We are now looking for a Senior Data Scientist to be responsible for developing AI/ML methods, processes, and systems to extract knowledge or insights to drive the future of artificial intelligence!! Provide data science tasks, perform advanced statistical analysis, and create insights into data to provide to the business actionable insights, identify trends, and measure performance which address business problems. Collaborate with business and process owners to understand business issues, and with engineers to implement and deploy scalable solutions, where applicable!! What You Will Do Apply and/or develop statistical modeling techniques (such as deep neural networks, Bayesian models, Generative AI, Forecasting), optimization methods and other ML techniques. Synthesize problems into data question(s). Convert data into practical insights. Analyze and investigate data quality for identified data and communicate it Product Owner, Business Analyst, and other relevant stakeholders. Collect Data, explore it, and perform analysis to extract information suitable to the business need. Identify gaps in the data, aggregate data as per business need. Design & perform Data Analysis, Data Validation, Data Transformation, Feature Extraction. Decide approach for addressing business needs with Data & analytics. Understand end user needs and work accordingly with identifying new features in the data. Develop Data Science and Engineering Infrastructure &Tools. Derive key metrics suitable for the use-case and present the analysis to key stakeholder. You will bring 4-8 years of relevant Industry experience. A Bachelor’s or higher degree in Computer Science, Statistics, Mathematics, or related disciplines. Ability to analyse data and communicate outcome to key stakeholders exploring new data source Excellent coding skills in python, R, SQL etc. Understanding of cloud services. Evidence of academic training in Statistics. Deep/broad knowledge of machine learning, statistics, optimization, or related field A genuine curiosity about new and applied technology and software engineering coupled with a high degree of business understanding. Experience in large scale product development is a plus. Experience in Generative AI and Large Language Models Why join Ericsson? At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more. Primary country and city: India (IN) || Kolkata Req ID: 768998

Join our Team About this opportunity We are now looking for a Senior Data Scientist to be responsible for developing AI/ML methods, processes, and systems to extract knowledge or insights to drive the future of artificial intelligence!! Provide data science tasks, perform advanced statistical analysis, and create insights into data to provide to the business actionable insights, identify trends, and measure performance which address business problems. Collaborate with business and process owners to understand business issues, and with engineers to implement and deploy scalable solutions, where applicable!! What you will do Apply and/or develop statistical modeling techniques (such as deep neural networks, Bayesian models, Generative AI, Forecasting), optimization methods and other ML techniques. Synthesize problems into data question(s). Convert data into practical insights. Analyze and investigate data quality for identified data and communicate it Product Owner, Business Analyst, and other relevant stakeholders. Collect Data, explore it, and perform analysis to extract information suitable to the business need. Identify gaps in the data, aggregate data as per business need. Design & perform Data Analysis, Data Validation, Data Transformation, Feature Extraction. Decide approach for addressing business needs with Data & analytics. Understand end user needs and work accordingly with identifying new features in the data. Develop Data Science and Engineering Infrastructure &Tools. Derive key metrics suitable for the use-case and present the analysis to key stakeholder. You will bring 4-8 years of relevant Industry experience. A Bachelor’s or higher degree in Computer Science, Statistics, Mathematics, or related disciplines. Ability to analyse data and communicate outcome to key stakeholders exploring new data source Excellent coding skills in python, R, SQL etc. Understanding of cloud services. Evidence of academic training in Statistics. Deep/broad knowledge of machine learning, statistics, optimization, or related field A genuine curiosity about new and applied technology and software engineering coupled with a high degree of business understanding. Experience in large scale product development is a plus. Experience in Generative AI and Large Language Models Why join Ericsson? At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more. Primary country and city: India (IN) || Kolkata Req ID: 768998

Description We are seeking a highly skilled and motivated Data Scientist with expertise in leveraging data to inform business strategy and drive product innovations. In this role, you will apply your expertise in machine learning and analytics. As Data Scientist you will play a crucial role in developing and implementing innovative solutions that leverage AI/ML platform to extract valuable insights from complex data sets. Your work will contribute to enhancing our data-driven decision-making processes and advancing our products and services. Responsibilities: Improve the performance of RCM processes by building and launching machine learning models such as insurance eligibility prediction Design, execute, and analyze A/B testing experiments to measure model performance and validate product hypotheses Define metrics and create dashboards to measure product performance Generate insights through deep-dive analysis to inform strategy and prioritization Collaborate with product, engineering, and marketing stakeholders to define the product roadmap Identify opportunities and initiate new data science projects that drive company OKRs Communicate technical insights effectively to influence decision-making Qualifications You have a Master’s degree in a relevant quantitative field (e.g. data science , computer science, statistics, economics) or equivalent in industry experience You have 5-8 years of experience as a data scientist supporting product development You are an expert in SQL You are proficient in either R or Python for data analysis You have successfully developed and launched ML models with quantifiable business impact You have experience designing and analyzing A/B testing experiments and guide product decisions with experimental insights You are results-driven and passionate about building great products, with a proven track record of taking projects from inception to launch Job Information Technology Primary Location India-Karnataka-Bengaluru Schedule: Full-time Travel: No Req ID: 251423 Job Hire Type Experienced Not Applicable #BMI N/A