Data Science Analyst

Numerator

Ex: 3 - 5 year

Full Time

Bengaluru East,Karnataka

3 - 5 years' progressive experience as a Data Analyst/BI engineer. Experience conducting large scale data analysis to support business decision making. Advanced knowledge of SQL with proven experience of using SQL for Analytics in a business environment. Demonstrated experience with BI tools such as Tableau, Power BI, Domo, etc.

Business Data Analyst – Python + SQL / Machine Learning / Data Science - Associate

JP Morgan Chase

Ex: 7+ years of work experience

Full Time

Bangalore,India

Alteryx, Tableau, SQL

Senior Associate-Data Science

Affine

Ex: 2.6 - 6

Full Time

pune,maharastra

Mid-Senior level

Analyst - Data Science

American express

Ex: Proven (0-3 years) experience as a Machine Learning Engineer, Research Engineer or similar role in solving practical business problems

Full Time

Bangalore,India

You Lead the Way. We’ve Got Your Back. At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways. Whether we’re supporting our customers’ financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly redefining what’s possible — and we’re proud to back each other every step of the way. When you join #TeamAmex, you become part of a diverse community of over 60,000 colleagues, all with a common goal to deliver an exceptional customer experience every day. Function Description: With a focus on digitization, innovation, and analytics, the Global Decision Sciences (GDS) team creates central, scalable platforms and customer experiences to help markets across all of these priorities. Charter is to drive scale for the business, and accelerate innovation for both immediate impact as well as long-term transformation of our business. A unique aspect of GDS is the integration of diverse skills across all of its remit. GDS has a very broad range of responsibilities, resulting in a broad range of initiatives around the world. The American Express AI Labs (AIL) is looking for research engineer for its Document Analytics and Intelligence Group in Bengaluru. AIL is a dynamic and rewarding workplace which started in 2012 and is currently co-located in Bangalore and New York and involves dynamic and talented researchers with Ph.D. or Master’s degree from top tier institutes in India and abroad having research and product development expertise in AI/ML technologies such as – Algorithms, Deep Learning, Machine Learning, Data Science, Natural Language Processing, Computer Vision, Product Management, Cloud Technologies and related technical areas. AIL’s Document Analytics & Intelligence (DAI) group is responsible for developing novel capabilities to read, understand, and interpret documents and provide bespoke AI solutions to power business analytics and automation use-cases. The key goal is to progress the state of the art and develop solutions for end-to-end business problems, in Document AI space, for American Express. Role Name: Analyst – Data Science – Amex AI Labs (Document Analytics & Intelligence Team). Purpose of the Role: Analyst – Data Science in Amex AI Labs work on cutting edge science and technology around Deep Learning, Data Science, NLP and Cloud technologies. The team works on challenging research problems at the intersection of NLP, Computer Vison, Machine Learning and Deep Learning. The key goal for an AI researcher is to enable next generation document intelligence to aid solutions to complex business problems for American Express Responsibilities: Research and implement appropriate AI/ML algorithms to solve complex business problems in Document AI space Development prototypes and innovative machine learning solutions according to the business requirements and demonstrate the efficacy to stake holders across different business units Work closely with business units to identify newer and rewarding opportunities for AI and automation in existing business processes Actively contribute to relevant scientific communities by extending existing ML libraries and frameworks, keep abreast of developments in the fields, publish scholarly articles and patents Critical Factors to Success (Outcome Driven): Business Outcomes: Innovate ways to evangelize the research outcome to drive significant value Contribute to the strategy and roadmap of AI/ML Initiatives to help drive most impact Work with business to identify innovation opportunities and ability to formulate the data science problems from the business requirements. Leadership Outcomes: Lead with an external perspective, challenge status quo and bring continuous innovation to push the boundaries of the state of the art Demonstrate learning agility, make decisions quickly and with the highest level of integrity Past Experience: Proven (0-3 years) experience as a Machine Learning Engineer, Research Engineer or similar role in solving practical business problems Academic Background: Bachelors/Masters/PhD in a quantitative field like Computer Science, Operations Research, Statistics etc. Functional Skills: Excellent written and verbal communication skills with the ability to collaborate Strong quantitative, analytical, and structured problem-solving skills. Demonstrate creativity and self-sufficiency along with strong interpersonal/ collaborative skills and experience working in global teams Track record of developing solutions leading to business benefits as well as inclination towards creation of intellectual property i.e., patents and papers in reputed conferences. Technical Skills: Strong hold on one or more of the following areas: Deep Learning, Machine Learning, Natural Language Processing, Document Processing, Image Processing, Computer Vision and related technical areas Hands on programming and ability to design algorithmic solutions using (one or more) Python, Java, C++, Scikit Learn, Git, Keras, PyTorch, Hive, Hadoop, Pyspark, SQL. Proficiency in Algorithms & Data Structures, Mathematical Modelling and Data Science, Advanced Statistical and machine learning techniques. Thorough knowledge of basics in math, statistics, and machine learning Experience in NLP, machine learning and deep learning techniques like unsupervised and supervised techniques-: active learning, transfer learning, neural models, Decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models. Boosting & bagging techniques, Loss functions, feature engineering, graph NN, RCNN, GCNN, BERT, Transformers etc. Knowledge of Platforms: Hand-on experience with scikit-learn, OpenCV, GIT, Hive, experience on deep learning platforms such as Keras, PyTorch etc. is desirable. Behavioral Areas: Enterprise Leadership Behaviors Set The Agenda: Put Enterprise Thinking First, Lead with an External Perspective Bring Others With You: Build the Best Team, Seek & Provide Coaching Feedback, Make Collaboration Essential Do It The Right Way: Communicate Frequently, Candidly & Clearly, Make Decisions Quickly & Effectively, Live the Blue Box Values, Great American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.