The Master of Science in Data Science is a postgraduate program that provides students with knowledge of the advanced fields of data analysis, statistics, machine learning and programming. It comes at a time when there is great demand for people with data knowledge across multiple industries including finance, health care, e-commerce and technology. The program ensures a strong theoretical basis in the subject area while also developing a range of practical skills that students can apply to extract meaningful information from large and complex data sets.
Admission to M.Sc. Data Science courses students are required to meet the academic entry specifications that usually require a bachelor degree in science, mathematics, engineering, computer sciences, or a related field. Most universities require 50 to 60% marks in their undergraduate degree. A mathematics or programming background is advised as it will be preferred. Some universities may also conduct entrance exams and/or hold interviews as part of the application process. Some top colleges that offer an M.Sc. in Data Science are IIT Madras, IIT Hyderabad, and IIT Roorkee, along with Christ University, NMIMS, Amity University, Jain University, and SRM University. Several of the colleges also offer M.Sc. in Data Science as part of their online, regular, or hybrid program.
Job options after completing an M.Sc. in Data Science are numerous and well-paid. The job title can be data scientist, data analyst, machine learning engineer, business intelligence analyst, and AI specialist, among others. Starting salary range is typically INR 5,00,000–INR 9,00,000 LPA, with experienced level graduates earning over INR 20,00,000 LPA. The demand for data-driven decision-making is expected to increase substantially in the future years, which is good news for graduates from M.Sc. in Data Science programs.
The M.Sc. Data Science is a two-year postgraduate qualification that helps students to develop expertise across other domains of data analytics. The curriculum includes learning topics across data analytics, machine learning, statistics, data visualization, and computer programming and plenty of practical application and engagement of these subjects into projects, case studies, and internships. Students will learn to understand and use an array of complex datasets to build predictive models that support data-driven decision-making. As the reliance of industries on data increases, graduates can pursue careers in analytics, software development, research, or data-centric business roles across a variety of industries.
Here are the key details about the M.Sc. Data Science Course Details:
| Feature | Description |
| Course Name | Master of Science in Data Science |
| Course Type | Postgraduate (PG) Degree |
| Duration | 2 years (4 semesters) |
| Mode of Study | Regular / Distance / Part-time / Online |
| Objective | To provide theoretical and practical knowledge of data handling, analysis, statistics, programming, and machine learning to solve real-world problems. |
| Core Subjects | Statistics, Probability, Data Mining, Machine Learning, Big Data Analytics, Data Visualization, Data Warehousing |
| Programming Languages Taught | Python, R, SQL, sometimes Java or Scala |
| Tools and Technologies | Tableau, Power BI, Hadoop, Spark, TensorFlow, NumPy, Pandas, Excel |
| Assessment Methods | Internal assignments, lab work, quizzes, semester exams, and capstone project |
| Project Work | Final semester project or dissertation (industry-linked or research-oriented) |
| Internship | Optional or mandatory depending on the university |
| Specializations (Optional) | AI & ML, Business Analytics, Healthcare Analytics, Financial Data Science, NLP |
M.Sc. Data Science eligibility criteria require students to have a bachelor's degree from a recognised university in any discipline based on science, computer applications, engineering, or mathematics/statistics. Admission into many institutions also requires an aggregate of 50 – 60 % marks. And a solid background in mathematics, coding or programming is preferred, depending on the institution and program. Many institutions allow a relaxation of the minimum percentage for candidates from reserved categories as defined by the Government guidelines. There should be no previous knowledge of statistics, coding, or handling data - but it would be beneficial.
Here are the key details about the M.Sc. Data Science Eligibility Criteria 2025:
| Criteria | Description |
| Educational Qualification | Bachelor’s degree (B.Sc., B.Tech, BCA, or equivalent) in Computer Science, IT, Mathematics, Statistics, Engineering, or related fields |
| Minimum Marks Required | 50% to 60% aggregate (varies by institution) |
| Subject Requirements | Mathematics/statistics/computer science in graduation is preferred or required |
| Final-Year Students | Eligible to apply provisionally |
| Programming Knowledge | Prior exposure to Python, R, or similar languages is beneficial |
| Bridge Courses | May be offered to non-CS/maths graduates to fill knowledge gaps |
| Additional Requirements (for some institutions) | Statement of Purpose (SOP), Letters of Recommendation, Resume |
M.Sc. Data Science admission is usually based on merit or entrance. All applicants must complete an online/ offline admission form and provide academic transcripts and other documents. Many popular institutions conduct their entrance tests or accept results of national-level entrance tests, such as CUET-PG. Some private universities provide direct admission based on undergraduate performance. After shortlisted applicants, they may invite shortlisted applicants for interviews, counseling rounds, etc. Admitted students must show relevant documents and pay the fees for confirmation.
Here are the key details about the M.Sc. Data Science Admission Process 2025:
| Stage | Description |
| Application Submission | Apply through university portals or centralized portals (CUET-PG, state-level) |
| Documents Required | Graduation marksheets, ID proof, entrance exam score (if applicable), resume, SOP |
| Entrance Exam | May be required by many universities (e.g., CUET-PG, GATE, university-specific tests) |
| Shortlisting | Based on merit or entrance score |
| Interview / GD | Some universities conduct personal interviews or group discussions |
| Final Selection | Based on cumulative performance in written test, academics, and interview |
| Admission Confirmation | Offer letter is issued; students must pay the fee to confirm admission |
Many universities or colleges also conduct entrance examinations for M.Sc. Data Science admissions. The major M.Sc. Data Science entrance exam are CUET-PG, BHU PET, and other university specific entrance admission tests. The entrance exams will usually evaluate candidates in quantitative aptitude, logical reasoning, basic programming, statistics, and familiarity with the English language. Entrance tests are usually multiple-choice and done online. Candidates who are applying and expecting to apply for top government and private institutions should be prepared. Some online or part-time programs may not require entrance exams if the candidates have good marks or work experience.
Here are the key details about the M.Sc. Data Science Entrance Exam 2025:
| Exam Name | Conducting Body | Applicable For | Exam Pattern | Syllabus Focus | Difficulty Level |
| CUET-PG | NTA (National Testing Agency) | Central and state universities | MCQs, 2 hours | General Aptitude, Logical Reasoning, Mathematics, Data Interpretation | Moderate |
| GATE | IITs and IISc | IITs, NITs (tech-focused programs) | Technical, 3 hours | Engineering Mathematics, Programming, Data Structures, Algorithms | High |
| JAM (Mathematics/Statistics) | IITs | Science-focused institutes | MCQ + Numerical | Pure Mathematics, Statistics, Logical Reasoning | High |
| TANCET | Anna University | Tamil Nadu-based universities | MCQ, 2 hours | Quantitative Aptitude, Logical Reasoning, Computer Awareness | Moderate |
| University-Specific Tests | Varies by university (e.g., BITS Pilani, Amity, SRM) | Private universities | Usually MCQ | Quant, Reasoning, Programming | Easy to Moderate |
The M.Sc. Data Science programs are available in a variety of formats in order to meet the needs of different learners. Full-time regular programs are intended for those who have recently received an undergraduate degree and want a smooth transition into the classroom experience. Online and distance learning options are designed for working professionals, and maintain flexibility with recorded lectures and online virtual labs. Various institutions also offer part-time and evening classes. The hybrid program combines both online learning with on occasion in-class learning experiences. Overall, all formats offer essentially the same content including expertise in programming, machine learning, and analytics.
Here are the key details about the Types of M.Sc. Data Science:
| Type | Mode | Duration | Target Audience | Flexibility | Institution Examples | Key Features |
| Regular | On-campus, full-time | 2 years | Fresh graduates, full-time students | Fixed schedule | IITs, NITs, University of Hyderabad, Christ University | Classroom learning, full-time interaction with faculty, access to labs |
| Distance | Remote with study centers | 2–3 years | Working professionals, remote learners | Moderate flexibility | IGNOU, Annamalai University | Self-paced learning with periodic contact classes |
| Part-Time | Evening/weekend classes | 2–3 years | Working professionals | Moderate | BITS Pilani (WILP), Jain University | Weekend lectures, project-based learning |
| Online | 100% remote, digital learning | 1.5–2 years | Anyone looking for remote education | High flexibility | IIIT Bangalore (via UpGrad), Great Learning, Coursera-affiliated universities | Recorded/live sessions, assignments, industry projects, career support |
The M.Sc. Data Science syllabus is usually divided into four semesters and consists of theoretical bases as well as practical training. The core topics include, statistics, probability, linear algebra coupled with different programming languages such us, Python and R. Other important topics include data mining, data visualization, Big Data Analytics, Machine learning and artificial intelligence. Advanced modules may include natural language processing, deep learning, Artificial Intelligence and cloud. Internships or research project as a component of the program, usually will occurs in your last semester, so that you can connect academic learning in authentic ways, and develop industry-ready skills.
Here are the key details about the M.Sc. Data Science Syllabus 2025:
| Semester | Core Subjects | Practical Components | Additional Modules |
| Semester 1 | Introduction to Data Science, Statistics and Probability, Linear Algebra, Python Programming, Data Structures and Algorithms | Python Lab, Statistics using R, Mini Project (Data Cleaning and EDA) | Communication Skills, Research Methodology |
| Semester 2 | Machine Learning I, Database Management Systems, Data Mining, Data Visualization, Big Data Technologies | SQL Lab, Tableau or Power BI Workshop, Hadoop or Spark Mini Project | Industry Seminar, Case Study Presentation |
| Semester | Core Subjects | Practical Components | Capstone or Project |
| Semester 3 | Machine Learning II, Deep Learning, Cloud Computing for Data Science, Natural Language Processing, Optimization Techniques | Python for Deep Learning Lab, NLP Project, AWS or GCP Practical | Internship Report, Technical Presentation |
| Semester 4 | AI Applications in Data Science, Elective I (e.g., FinTech Analytics), Elective II (e.g., Healthcare Analytics) | Elective Labs, Industry-focused Workshops | Final Capstone Project, Viva or Dissertation |
India has many top colleges that offering M.Sc. Data Science programs. Top M.Sc. Data Science private colleges include IIT Madras, IIT Hyderabad, Indian Statistical Institute (ISI), and University of Hyderabad. Prestigious private institutions include Christ University, NMIMS, Shiv Nadar University, and Ashoka University. These colleges have a track record of academic excellence, experienced faculty and promising placements. The admission process to most of these colleges is competitive and may involve an entrance examination and/or interview. Some of the best programs offer students practical exposure through internships, research projects, and student-industry partnerships. Graduates from these colleges are very much in demand by organisations in the analytics and data science space.
Here are the key details about the Top M.Sc. Data Science Colleges in India:
| College Name | Location | Key Features | Average Annual Fee | Admission Process |
| Indian Statistical Institute (ISI) | Kolkata | Highly research-focused, limited intake | INR 25,000 | Entrance Test and Interview |
| Christ University | Bangalore | Industry tie-ups, modern labs | INR 1.8 lakh | Merit and Entrance Exam |
| University of Hyderabad | Hyderabad | Strong academic curriculum, UGC recognized | INR 50,000 | CUET-PG |
| IIT Madras (via online mode) | Chennai | Offered in hybrid format, industry mentors | INR 1.5 lakh (total) | GATE or Direct Admission |
| Amity University | Multiple Cities | Global curriculum, corporate exposure | INR 2.5 lakh | Entrance Test or Merit-based |
India has several reputed institutions offering M.Sc. Data Science programs. Top M.Sc. Data Science private colleges include IIT Madras, IIT Hyderabad, Indian Statistical Institute (ISI), and University of Hyderabad. Prestigious private institutions include Christ University, NMIMS, Shiv Nadar University, and Ashoka University. These colleges are known for their academic excellence, experienced faculty, and strong placement records. Admission is usually competitive and may require entrance exams or interviews. The best programs provide practical exposure through internships, research opportunities, and industry collaboration. Graduates from these colleges are highly sought after by companies in the data science and analytics sectors.
Here are the key details about the Top M.Sc. Data Science Private Colleges in India:
| College Name | Location | Notable Aspects | Fee Structure | Placement Support |
| Vellore Institute of Technology (VIT) | Vellore | Strong placement network, research projects | INR 2 lakh | Yes, dedicated career services |
| SRM Institute of Science and Technology | Chennai | Skill-based training, data labs | INR 2.2 lakh | Good placement cell |
| MIT-WPU | Pune | Interdisciplinary electives, data tools training | INR 2.5 lakh | Industry collaborations |
| Jain University | Bangalore | Offers online and regular mode, cloud lab access | INR 1.8 lakh | Yes, for both on-campus and online students |
| Lovely Professional University (LPU) | Punjab | Dedicated analytics center, IBM partnership | INR 2 lakh | Active corporate tie-ups |
The M.Sc. Data Science government colleges include IIT Madras, IIT Hyderabad, NIT Trichy, Indian Statistical Institute (ISI), and the University of Hyderabad. These colleges are known for rigorous academic training, affordable fees, and employability. They provide good research infrastructure, experienced professors, and academic and industry linkages as well as international university partnerships. Admission is through entrance examinations such as CUET-PG or through college specific entrance tests, etc. Government colleges have some scholarships and financial aid for meritorious and weaker section students. Students graduating from these colleges have good repute in industry and academia and usually get a job in research, analytics, and high technology related organizations.
Here are the key details about the Top M.Sc. Data Science Government Colleges in India:
| College Name | Location | Academic Strength | Annual Fee | Admission Mode |
| University of Hyderabad | Hyderabad | Excellent research and faculty | INR 50,000 | CUET-PG |
| Banaras Hindu University (BHU) | Varanasi | Reputed central university | INR 30,000 | Entrance Exam |
| Savitribai Phule Pune University | Pune | Affordable, well-structured curriculum | INR 25,000 | Merit and Test |
| Delhi University (Select Colleges) | Delhi | Offers specializations via science stream | INR 20,000 to INR 40,000 | Merit or Departmental Test |
| Anna University | Chennai | Industry-academic integration, public research | INR 35,000 | TANCET or institutional test |
The M.Sc. Data Science fee structure depend on the institution as well as the mode of program delivery. Government colleges can charge between INR 20,000 and INR 1 lakh for a full academic year (Rs. 20k to 1 lakh), which makes it very reasonable. Private universities usually charge INR 1.5 to INR 6 lakhs for completion of the entire program depending on facilities, brand name, and other factors. And, for online programs, the overall fee probably lies between INR 50,000 to INR 2.5 lakhs. Students can apply for scholarships, education loans, or payment options by way of E.M.I.. A generational skill - even though there are exceptions, due to demand for statistics and data professionals/jobs in the marketplace, most people find solid returns on their investment.
Here are the key details about the M.Sc. Data Science Fee Structure 2025:
| Type of Institution | Annual Fee Range | What’s Included | Additional Costs | Scholarship & Financial Aid |
| Government/Public Universities | INR 20,000 to INR 80,000 | Tuition, library access, lab facilities, academic support | Hostel charges (INR 10,000–INR 30,000), exam fees, personal equipment or study materials | Scholarships available for reserved categories, economically weaker sections, and meritorious students |
| Private Universities/Colleges | INR 1.2 lakh to INR 3.5 lakh | Tuition, lab access, career services, workshops, seminars | Hostel (INR 50,000–INR 1 lakh), optional certifications, industry visits, study materials | Merit-based, need-based, sports and alumni-sponsored scholarships are often available |
| Distance Learning Programs | INR 50,000 to INR 1.5 lakh (total) | Online course content, digital labs, recorded lectures, discussion forums | Exam fees, certification charges, optional workshops or residencies | EMI options, corporate-sponsored reimbursement, and need-based discounts may apply |
| Online/Hybrid Programs | INR 1 lakh to INR 2.5 lakh (total) | Interactive classes, projects, cloud labs, mentorship, placement support | Extra for live bootcamps, tools access, printed materials | Installment plans, referral discounts, early-bird discounts available |
| Autonomous Institutes (e.g., ISI, IISc) | INR 25,000 to INR 1 lakh | Core teaching, lab infrastructure, project support | Accommodation, travel, specialized software (if needed) | Government fellowships, institute-specific merit scholarships |
M.Sc. Data Science graduates have various career options in the private and public sector, including where employment opportunities exist- entry-level data scientist, data analyst, machine learning engineer, business analyst, AI specialist, or research associate, to name a few. M.Sc. Data Science job opportunities in banking, healthcare, e-commerce, education, and government research organizations, are constantly looking for data professionals, as well as non-governmental organizations (NGOs). Many other freelance and consulting opportunities are being advertised as only research or consulting organizations, increasingly relying on complex datasets and embedding thought in daily decision-making processes.
Here are the key details about the M.Sc. Data Science Career Opportunities:
| Job Role | Key Responsibilities | Skills Required | Industries Hiring | Growth Prospects |
| Data Scientist | Analyze large data sets, build predictive models, uncover patterns and trends | Python, R, Machine Learning, Statistics, SQL | IT, Finance, Healthcare, E-commerce | High; transition to Senior Data Scientist, AI Lead |
| Data Analyst | Interpret data, create dashboards, assist in data-driven decisions | Excel, SQL, Data Visualization (Tableau, Power BI), Python | Retail, Logistics, Banking | Moderate; can move to Business Analyst or Data Scientist |
| Machine Learning Engineer | Design and deploy ML models into production | ML Algorithms, TensorFlow, Python, Deployment Tools | Technology, Cybersecurity, EdTech | High; potential to become AI/ML Architect |
| Business Analyst | Bridge between data team and business stakeholders, provide actionable insights | Domain Knowledge, Communication, Analytics, SQL | FMCG, Finance, Consulting | High; can grow into Strategy or Product roles |
| Data Engineer | Develop data pipelines, manage databases, enable real-time processing | Hadoop, Spark, SQL, Data Warehousing | Telecom, Streaming, IT | High; next roles include Lead Data Engineer |
| AI Specialist | Develop intelligent systems, NLP tools, image recognition models | Deep Learning, Neural Networks, Python, NLP | Defense, Robotics, Healthcare | Very High; can progress to AI Research Scientist |
| Quantitative Analyst | Use mathematical models to assess financial risks or opportunities | Statistics, R, Python, Financial Modeling | Investment Banking, Insurance, FinTech | High; roles in risk management and hedge funds |
| Data Consultant | Advise companies on data strategy, integration, and analytics-based decision-making | Analytical Thinking, Industry Expertise, Visualization Tools | Consulting Firms, Startups | Flexible; scope to start own consultancy |
| Research Scientist (AI/DS) | Work on cutting-edge innovations, publish findings, develop proprietary algorithms | Academic Research, Python, MATLAB, Publication Writing | Academia, R&D Labs | High; roles in postdoc and think tanks |
M.Sc. Data Science salary is depend a lot onexperience, skill levels and the employer. For an entry-level data analyst or data scientist, salary generally ranges from INR 5 to INR 9 lakh per annum. Upon gaining 3-5 years of commercial experience, the expected salary is between INR 12 and INR 20 lakh per annum. In the case of large organisations, situation with data-engineering, AI or data architect roles, one may earn INR 25 lakh or more. Top India employers are generally huge multinationals such as Amazon, Accenture, Deloitte and consulting firms like TCS and Infosys. Salaries are likely higher with companies located in metro cities such as Bengaluru, Hyderabad or Mumbai, so consider relocation.
Here are the key details about the M.Sc. Data Science Salary in India:
| Job Role | Entry-Level (0–2 yrs) | Mid-Level (3–6 yrs) | Senior-Level (7+ yrs) | Remarks |
| Data Scientist | INR 6 – INR 10 LPA | INR 12 – INR 20 LPA | INR 25 LPA and above | Salaries vary based on domain (e.g., finance pays higher) |
| Data Analyst | INR 4 – INR 7 LPA | INR 8 – INR 12 LPA | INR 15 – INR 18 LPA | Excel + Tableau + SQL are must-have tools |
| ML Engineer | INR 7 – INR 12 LPA | INR 15 – INR 25 LPA | INR 30 LPA and above | High growth due to AI boom |
| Business Analyst | INR 5 – INR 9 LPA | INR 10 – INR 15 LPA | INR 18 – INR 25 LPA | Domain knowledge adds significant value |
| Data Engineer | INR 6 – INR 11 LPA | INR 14 – INR 20 LPA | INR 25 – INR 30 LPA | Cloud and Big Data knowledge are key |
| AI Specialist | INR 8 – INR 14 LPA | INR 18 – INR 28 LPA | INR 35 LPA and above | NLP, Vision, and Speech models fetch top salaries |
| Quantitative Analyst | INR 7 – INR 12 LPA | INR 15 – INR 22 LPA | INR 28 – INR 40 LPA | Mostly in BFSI and hedge funds |
| Research Scientist | INR 6 – INR 10 LPA | INR 12 – INR 18 LPA | INR 20 – INR 30 LPA | PhD or publication record may boost offers |
In India, the scope of M.Sc. Data Science is very large, as every industry is going through a rapid digital transformation with the rise of data consumption and data-driven problem solving. Industries such as finance, healthcare, education, agriculture, and government are spending trillions of dollars on data-driven solutions, which allows multiple paths for graduates. They can go on to be data analysts, machine learning engineers, researchers, business intelligence developers, automation developers and more. Academic careers are also expanding. Many students go on to pursue PhD programs and that includes research and fellowship opportunities outside of their own countries.
Here are the key details about the M.Sc. Data Science Scope in India:
| Area | Details | Growth Drivers | Future Outlook |
| IT & Software | High demand for data scientists, ML engineers, and cloud data specialists | Cloud computing, AI, mobile data explosion | Strong upward trend expected over next decade |
| Banking & Finance | Data analytics for fraud detection, credit scoring, and risk modeling | Digital payments, FinTech rise, compliance needs | Highly data-driven, increasing demand for data roles |
| Healthcare & Pharma | Predictive diagnostics, clinical data analysis, and drug discovery | EHR systems, genomics, telemedicine | Rapid growth in health data research |
| Retail & E-commerce | Customer behavior analysis, sales forecasting, recommendation systems | Online retail boom, consumer personalization | Vital for business growth strategies |
| Telecom & IoT | Real-time analytics, usage pattern analysis, customer churn prediction | 5G deployment, smart devices, sensor data explosion | Core to network optimization and monetization |
| Government & Policy | Public data utilization, smart cities, crime data analysis | Digital India mission, open data portals | Emerging area with policy-focused data roles |
| Education & EdTech | Personalized learning, academic performance analytics | E-learning platforms, digital assessments | AI-driven learning models growing fast |
| Startups & Innovation | AI/ML-based services, deep tech R&D, platform-based analytics solutions | Funding ecosystem, incubators, innovation hubs | Fastest-growing sector for fresh graduates |
There are several M.Sc. Data Science top recruiters including large tech companies like TCS, Infosys, Wipro, HCL, Accenture and IBM, alongside technology giants like Amazon, Google, Microsoft and Facebook for data roles. Consulting companies such as Deloitte, EY, PwC, and KPMG also hire analytics and business intelligence roles. Fintech, health tech, edtech, and startups are all hiring data science roles in AI/predictive modeling. E-commerce giants like Flipkart and Myntra are also hiring M.Sc. Data Science graduates in data analyst and data engineering roles. There are also opportunities in research (Ngos), governments, and others in need of skilled professionals in data science.
Here are the key details about the M.Sc. Data Science Top Recruiters:
| Company/Organization | Industry | Roles Offered | Why They Hire Data Scientists |
| Tata Consultancy Services (TCS) | IT Services | Data Analyst, AI Developer, Business Intelligence Analyst | To power enterprise solutions with analytics |
| Infosys | IT & Consulting | Data Engineer, Machine Learning Engineer | For client-driven analytics projects |
| IBM India | Technology | AI Specialist, Data Scientist, Research Associate | Core AI division and consulting analytics |
| Amazon | E-commerce, Cloud | Data Scientist, Business Analyst, Operations Research Scientist | For customer behavior modeling and supply chain optimization |
| Google India | Technology | Data Engineer, AI Researcher, Product Analyst | Heavy reliance on user data and AI modeling |
| Wipro | IT Services | Data Science Consultant, Automation Engineer | Focus on AI in enterprise automation |
| Accenture | Consulting | Applied Intelligence Analyst, Data Strategy Consultant | AI and analytics division supports global clients |
| J.P. Morgan & Chase | Banking & Finance | Quantitative Analyst, Risk Analyst, Data Scientist | Financial modeling, algorithmic trading |
| Flipkart | E-commerce | Data Analyst, Personalization Engineer | User behavior, logistics, recommendation systems |
| Zomato/Swiggy | Food Tech | Customer Insights Analyst, Demand Prediction Engineer | Real-time pricing, consumer analytics |
| ISRO / DRDO | Government / R&D | Scientific Analyst, Data Researcher | Data analytics for space and defense systems |
| EY / Deloitte | Consulting / Audit | Data Analyst, AI Strategy Analyst | Risk and forensic analytics, client advisory |
| Startups (e.g., Razorpay, CRED, Dunzo) | FinTech, Logistics, EdTech | Full-stack Data Scientist, ML Product Lead | Product-focused innovation using AI/ML |
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