Applied Data Scientist/ Data Science Engineer

Job ID: SRJ_7996Posted: 2025-12-04Location: Austin, TXSalary: USD 145-150 / Yearly (Full Time)Employment Type: Full TimeIndustry: Computer SoftwareClient: WiproContact: Meghana GorusuCompany: SRI Tech SolutionsRole: Applied Data Scientist/ Data Science EngineerLocation: Austin, TX (3 Days onsite/week)Yrs. of experience: 8+ Yrs.Interview Process:We are only looking for profiles who can relocate to Austin, TX or local to Austin, TX.Job Responsibilities:You will be part of a team that innovates and collaborates with internal stakeholders to deliver world-class solutions with a customer first mentality. This group is passionate about the data science field and is motivated to find opportunity in, and develop solutions for, evolving challenges.You will:Solve business and customer issues utilizing AI/ML - MandatoryBuild prototypes and scalable AI/ML solutions that will be integrated into software productsCollaborate with software engineers, business stakeholders and product owners in an Agile environmentHave complete ownership of model outcomes and drive continuous improvementEssential Requirements:Strong coding skills in Python and SQL - MandatoryMachine Learning knowledge (Deep learning, Information Retrieval (RAG), GenAI , Classification, Forecasting, Regression, etc. on large datasets) with experience in ML model deploymentAbility to work with internal stakeholders to transfer business questions into quantitative problem statementsAbility to effectively communicate data science progress to non-technical internal stakeholdersAbility to lead a team of data scientists is a plusExperience with Big Data technologies and/or software development is a plusDesirable Requirements:Masters or PhD in a quantitative disciplineSRI Tech Solutions is an equal opportunity employer and does not discriminate on the basis of race, color, gender, religion, age, sexual orientation, national origin or citizenship status or ethnic origin, disability, marital status, veteran status, or any other occupationally irrelevant criteria.