Data Scientist

Job Description

At (TekLink HGS Digital), our vision is to be the globally preferred digital transformation partner for our clients, creating value in their business through rigorous innovation at scale. We are an expert team of 500+ leading strategic thinkers, digital marketing and creative masters, data analysts, software engineers, and process optimization specialists with an elemental desire to create transformative digital solutions. Job Title: Data Scientist Location: Hyderabad, India Duration: Full time Data scientist would support our internal teams and clients in driving strategic decisions, applying advanced statistical & predictive analytics and machine learning concepts to solve business problems in BFSI and CPG domains. You will also phrase requirements document, contribute towards project plan, carry out data research and collection, study attributes and features, test for parameters, resolve data issues, decide on models, modeling, QA/testing and showcase the findings in various formats for client consumption. Responsibilities: a) Analytics Requirements Definition: Works with business users to approve the requirements for analytics solution. b) Data Preparation: Reviews data preparation rules (data extraction, data integration, data granularity, data cleansing etc.). Prepares data for analytical modelling. Guides data analysts and associate data scientists on data preparation activities. c) Builds Machine Learning (ML) and Statistical Models using Python/R/Scala/SAS/SPSS d) Collaborate with clients and internal teams to define industry-leading analytics solutions for a wide variety of industries and business groups e) Develop proof-of-concepts and demos needed for client & internal presentations f) Create clear functional and technical documentation g) Work agnostic across multiple industry sectors and functional domains, with focus on BFSI and CPG domains. h) Work closely with all stakeholders to identify, evaluate, design, and implement statistical and other quantitative approaches for modeling enterprise scale data and big data i) Display proficiency in converting algorithmic proof of concepts into business requirement documents for product development or data driven actionable intelligence Minimum Requirements & Qualification The ideal candidate should have: • Full time Degree in Mathematics, Statistics, Computer Science or Computer Applications from reputed institutions, B.E./B.Tech., MBA specialized in Marketing, Operations Research, Data Science and/or Business Analytics • Overall 8+ years of technical experience in IT industry across BFSI and CPG domains. • Minimum of 5 years of hands-on work experience in Data Science/Advance analytics, Machine Learning using Python and SQL • Practical experience specifically around quantitative and analytical skills is required. • People management skills and experience, and familiarity with the pharmaceutical industry are preferred. • Knowledge of solution design, planning, and execution • Contribute to case studies, blogs, eBooks, and whitepapers • Proficiency in maintaining strong project documentation hygiene • Able to fully assimilate into automated MLOps mode • Must have good communication skills – written, oral, ppt and language skills o Able to translate statistical findings to business English • Hands on experience in one or more of the skillsets below: o Programming Language: R Programming, Base SAS, Advanced SAS o Visualization Tool: Tableau, MS Excel, think-cell, Power BI, Qlik Sense o Automation Tool: VBA Macro, Python scripts • Basic understanding of NLP/NLU/NLG and text mining • Skills/knowledge of advanced ML techniques with image processing and signal processing is a plus • GenAI and multimodal GenAI skills with RAG development and fine tuning • Sounds statistical training in linear and non-linear regression, weighted regression, clustering, and classification techniques • Sound understanding of applied statistical methods including survival analysis, categorical data analysis, time series analysis and multivariate statistics • Introduction to classical statistical including concepts in Bayesian statistics, experimental design and inference theory • Practical understanding of concepts in computer vision, data mining, machine learning, information retrieval, pattern recognition and knowledge discovery • Additional knowledge in WFM, biological learning systems and modern statistical concepts is a plus • Knowledge of IoT devices and solutions with multi-sensor data fusion is a plus • Knowledge of Geostatistics, information theory, computational statistics is a plus • Experience in character recognition with image, speech, and video analytics capabilities is a plus • Working knowledge of or certifications in AWS/Azure/GCP is beneficial