Data Science Architect - Machine Learning & Data Mining

Job Responsibilities : - Data mining using state-of-the-art methods - Enhancing data collection procedures to include information that is relevant for building analytic systems - Processing, cleansing, and verifying the integrity of data used for analysis - Doing ad-hoc analysis and presenting results in a clear manner - Creating automated anomaly detection systems and constant tracking of its performance - Selecting features, building and optimizing classifiers using machine learning techniques - Responsible for defining and documenting architecture, capturing and documenting non-functional (architectural) requirements, preparing estimates and defining technical solutions to proposals (RFPs) - Provide technical leadership to project team to perform design to deployment related activities, provide guidance, perform reviews, prevent and resolve technical issues - Analyses complex business and competitive issues and discerns the implications for systems support. - Identifies, defines, directs and preforms analysis of technical and economic feasibility of proposed data solution. - Creates and manages a machine learning pipeline, from raw data acquisitions to merging and normalizing to sophisticated feature engineering development to model execution. - Designs, leads and actively engages in projects with broad implication for the business and/or the future architecture, successfully addressing cross-technology and cross-platform issues Selects tools and methodologies for projects and negotiates terms and conditions with vendors. - Communicates highly technical information to numerous audiences, including senior management, the user community, and less-experiences staff. - Leads the organizations planning for the future of the data model and data architecture. - Exhibit advanced visualization skills, as well as creative problem-solving - Interacting with customers to have an in-depth understanding of their operations to improve their processes for managing equipment and interfacing. - Reviewing and providing counsel for all major "Business Case Analysis" effort. - Developing the interdependencies between major applications/efforts - Providing project leadership, advice, and counsel to developers, management, customers and project teams on the most complex aspects of application development and system integration. Basic (Required) Qualifications : - A Bachelor- s Degree from an accredited college or university or equivalent years (4 years) of experience relevant to this role. - Seven or more years of progressively responsible role relevant experiences that demonstrate both breadth of business knowledge and depth of digital and analytical skillsets. - Curiosity about and a deep interest in how digital technology and systems are powering the way users do their jobs. - Comfortable working in a dynamic environment where digital is still evolving as a core offering. - Ability to clearly and succinctly explain complex topics. - Expert in Python; familiar with concurrency in Python - Track record of architecting and delivering highly available back end systems for large-scale consumer experiences - Proficient with git or similar source control system; and Experienced with git-based development workflows - Ability to design and consume well-tailored REST APIs - Experience working in development teams with code reviews and varying levels of seniority - Thrives in agile environments but also understands the balance in coding discipline required for large scale, high quality end consumer apps - Experience both in jumping in to an existing architecture, and starting projects from scratch - Proven ability to take initiative and dive in to areas of new technology - Self-motivated with a passion for learning, analysing technology trade-offs, and shipping product - Good applied statistics skills, such as distributions, statistical testing, regression, etc. - Proficiency in using query languages such as SQL - Good scripting and programming skills - Data-oriented personality Desired Qualifications : - Experience with common data science toolkits, such as Python, R, Weka, Matlab, etc (Excellence in at least one of these is highly desirable). - Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. - Experience with data visualisation tools, such as Tableau, Power BI, D3.js, GGplot, etc. - Experience with NoSQL databases, such as MongoDB, Cassandra, HBase (ref:hirist.tech)

Location: in, IN

Posted Date: 4/3/2025