Assistant Manager - Data science Major Duties & Responsibilities Work with business stakeholders and cross-functional SMEs to deeply understand business context and key business questions Create Proof of concepts (POCs) / Minimum Viable Products (MVPs), then guide them through to production deployment and operationalization of projects Influence machine learning strategy for Digital programs and projects Make solution recommendations that appropriately balance speed to market and analytical soundness Explore design options to assess efficiency and impact, develop approaches to improve robustness and rigor Develop analytical / modelling solutions using a variety of commercial and open-source tools (e.g., Python, R, TensorFlow) Formulate model-based solutions by combining machine learning algorithms with other techniques such as simulations. Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories. Create algorithms to extract information from large, multiparametric data sets. Deploy algorithms to production to identify actionable insights from large databases. Compare results from various methodologies and recommend optimal techniques. Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories. Develop and embed automated processes for predictive model validation, deployment, and implementation Work on multiple pillars of AI including cognitive engineering, conversational bots, and data science Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment Provide guidance and leadership to more junior data scientists, managing processes and flow of work, vetting designs, and mentoring team members to realize their full potential Lead discussions at peer review and use interpersonal skills to positively influence decision making Provide thought leadership and subject matter expertise in machine learning techniques, tools, and concepts; make impactful contributions to internal discussions on emerging practices Facilitate cross-geography sharing of new ideas, learnings, and best-practices Required Qualifications Bachelor of Science or Bachelor of Engineering at a minimum. 7 years of work experience as a Data Scientist A combination of business focus, strong analytical and problem-solving skills, and programming knowledge to be able to quickly cycle hypothesis through the discovery phase of a project Advanced skills with statistical/programming software (e.g., R, Python) and data querying languages (e.g., SQL, Hadoop/Hive, Scala) Good hands-on skills in both feature engineering and hyperparameter optimization Experience producing high-quality code, tests, documentation Experience with Microsoft Azure or AWS data management tools such as Azure Data factory, data lake, Azure ML, Synapse, Databricks Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine learning algorithms, optimization & forecasting techniques, and / or deep learning methodologies Proficiency in statistical concepts and ML algorithms Good knowledge of Agile principles and process Ability to lead, manage, build, and deliver customer business results through data scientists or professional services team Ability to share ideas in a compelling manner, to clearly summarize and communicate data analysis assumptions and results Self-motivated and a proactive problem solver who can work independently and in teams Preferred Qualifications Experience working in one or multiple supply chain functions (e.g., procurement, planning, manufacturing, quality, logistics) is strongly preferred Experience in applying AI/ML within a CPG or Healthcare business environment is strongly preferred Exposure to Pyomo, Mosel, truck load optimization, multi-echelon inventory optimization (MEIO) Experience in NLP, Vision, and/or AR / VR Experience in creating CI/CD pipelines for deployment using Jenkins. Experience implementing MLOPs framework along with understanding of data security implementation on ML models Hands on experience developing ML driven models Categories Data Engineer (Software and Web Development) Business Analysts (Information Design and Documentaion) Data Scientist (Software and Web Development) ML/AI Engineers (Software and Web Development) Customer Support Representatives (Customer Service and IT Operations) Must Have Skills Data Science - 5 Years : Intermediate Python - 3 Years : Intermediate SQL - 3 Years : Intermediate Hadoop - 3 Years : Intermediate Apache Hive - 3 Years : Intermediate Apache Scala - 3 Years : Intermediate Azure - 2 Years : Intermediate AWS - 2 Years : Intermediate Machine Learning - 3 Years : Intermediate (ref:hirist.tech),
Employement Category:
Employement Type: Full time Industry: IT Services & Consulting Role Category: Not Specified Functional Area: Not Specified Role/Responsibilies: Assistant Manager - Data Science Job in Crazy
Contact Details:
Company: Crazy Solutions Location(s): Other Karnataka