2627 Data Science Jobs - Page 38

About the Role As a Data Science Engineer, you will need strong technical skills in data modeling, machine learning, data engineering, and software development. You will have the ability to conduct literature reviews and critically evaluate research papers to identify applicable techniques. Additionally, you should be able to design and implement efficient and scalable data processing pipelines, perform exploratory data analysis, and collaborate with other teams to integrate data science models into production systems. Passion for conversational AI and a desire to solve some of the most complex problems in the Natural Language Processing space are essential. You will work on highly scalable, stable, and automated deployments, aiming for high performance. Taking on the challenge of building and scaling a truly remarkable AI platform to impact the lives of millions of customers will be part of your responsibilities. Working in a challenging yet enjoyable environment, where learning new things is the norm, you should think of solutions beyond boundaries. You should also drive outcomes with full ownership, deeply believe in customer obsession, and thrive in a fast-paced environment of learning and innovation. You will work in a challenging, consumer-facing problem space, where you can make an immediate impact. You will get to work with the latest technologies, learn to use new tools and get the opportunity to have your say in the final product. Youll work alongside a great team in an open, collaborative environment. We are part of Vimo, a well-funded, stable mid-size company with excellent salaries, medical/dental/vision coverage, and perks. Vimo is an Equal Opportunity Employer. Data Science Engineer Responsibilities: Build and maintain robust data pipelines to process data from varied sources like databases, APIs, and file systems. Harness data science tools and techniques to develop proof of concepts, evolving solutions through adept prompt engineering and fine-tuning of models like GPT. Conduct comprehensive literature reviews and critically evaluate research papers to identify innovative techniques, focusing on the latest advancements in LLM/Generative AI. Create and manage JSON APIs to expose data, machine learning services, and AI models to other systems and applications. Ensure data accuracy, completeness, and reliability through stringent quality control measures and data validation techniques. Optimize existing language models for generative AI tasks, focusing on enhancing their application across various platforms. Work in tandem with product teams to seamlessly integrate cutting-edge AI technologies, upholding the highest quality standards in product execution. Fine-tune and deploy LLMs, ensuring they are meticulously adjusted and ready for release. Engage in ongoing research and application of new methodologies to bolster the efficiency and output quality of our LLM operations. Design and develop LLMs dedicated to a range of content generation tasks, pushing the boundaries of AI's creative capabilities. Keep up to date of the latest trends and breakthroughs in NLP and large language model technology, incorporating novel approaches to refine our models. Lead experiments and analyses to fine-tune model designs and hyperparameters, ensuring superior model performance with continuous monitoring using KPIs and metrics. Demonstrate strong analytical and troubleshooting skills; and someone who enjoys owning and solving problems end-to-end. Excellent communication skills. Comfortable interacting with remote teams in multiple offices that practice agile methodologies. Requirements & Qualifications: Bachelors or masters degree in computer science, Engineering, Mathematics, Statistics, or a related field. Minimum of 2 years of experience in NLP oriented data engineering or data science roles with a significant emphasis on working with LLM/Generative AI models. Robust understanding of NLP concepts, with hands-on experience in conversational AI and expertise in natural language understanding and generation. Proficiency in Python programming and familiarity with libraries and frameworks such as Pandas, NumPy, Scikit-learn, Tensor flow, transformers, PyTorch, and Keras. Solid experience in building, maintaining, and fine-tuning large language models, with a keen understanding of prompt engineering techniques. Strong grasp of data architecture, database design, data modeling principles, and the integration of AI models into scalable systems. Experience with JSON APIs and building RESTful & GRPC web services. Excellent analytical and problem-solving skills, capable of working independently and collaboratively in a team-oriented environment. Showcase proven expertise in working with deep learning frameworks and LLMs, with a strong foundation in prompt engineering, tokenization, embeddings, model optimization, and deployment strategies. Demonstrate previous involvement in creating user-centric products leveraging ML/AI technologies, with a good understanding of predictive modeling, meta-learning, and transfer learning. Excellent problem-solving and communication skills BS degree in Information Technology, Computer Science, or relevant field Additional Experience We Would Love to Have Experience with cloud technologies such as AWS is a plus. Background in design and development of Technology for Government Health and Human Services Experience with design and development of SaaS solutions.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Skills: Machine Learning, Data Science, Azure, Python, Hadoop. Roles and Responsibilities: Strong understanding of Math, Statistics, and the theoretical foundations of Statistical & Machine Learning, including Parametric and Non-parametric models. Apply advanced data mining techniques to curate, process, and transform raw data into reliable datasets. Use various statistical techniques and ML methods to perform predictive modeling/classification for problems related to clients, distribution, sales, client profiles, and segmentation, and provide actionable insights for business decision-making. Demonstrate expertise in the full Machine Learning lifecycle--feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loops. Proficiency in Python visualization libraries such as matplotlib and seaborn. Experience with cloud computing infrastructure like Azure, including Machine Learning Studio, Azure Data Factory, Synapse, Python, and PySpark. Ability to develop, test, and deploy models on cloud/web platforms. Excellent knowledge of Deep Learning Architectures, including Convolutional Neural Networks and Transformer/LLM Foundation Models. Strong expertise in supervised and adversarial learning techniques. Robust working knowledge of deep learning frameworks such as TensorFlow, Keras, and PyTorch. Excellent Python coding skills. Experience with version control tools (Git, GitHub/GitLab) and data version control. Experience in end-to-end model deployment and productionization. Demonstrated proficiency in deploying, scaling, and optimizing ML models in production environments with low latency, high availability, and cost efficiency. Skilled in model interpretability and CI/CD for ML using tools like MLflow and Kubeflow, with the ability to implement automated monitoring, logging, and retraining strategies. Experience Requirement: 5-12 years of experience in designing and deploying deep learning and machine learning solutions. Proven track record of delivering AI/ML solutions in real-world business applications at scale. Hands-on experience working in cross-functional teams including data engineers, product managers, and business stakeholders. Experience mentoring junior data scientists and providing technical leadership within a data science team. Experience working with big data tools and environments such as Hadoop, Spark, or Databricks is a plus. Prior experience in managing model lifecycle in enterprise production environments including drift detection and retraining pipelines. Education: B.Tech.

What you’ll do: Utilize advanced mathematical, statistical, and analytical expertise to research, collect, analyze, and interpret large datasets from internal and external sources to provide insight and develop data driven solutions across the company Build and test predictive models including but not limited to credit risk, fraud, response, and offer acceptance propensity Responsible for the development, testing, validation, tracking, and performance enhancement of statistical models and other BI reporting tools leading to new innovative origination strategies within marketing, sales, finance, and underwriting Leverage advanced analytics to develop innovative portfolio surveillance solutions to track and forecast loan losses, that influence key business decisions related to pricing optimization, credit policy and overall profitability strategy Use decision science methodologies and advanced data visualization techniques to implement creative automation solutions within the organization Initiate and lead analysis to bring actionable insights to all areas of the business including marketing, sales, collections, and credit decisioning Develop and refine unit economics models to enable marketing and credit decisions What you’ll need: 5 to 8 years of experience in data science or a related role with a focus on Python programming and ML models. Strong in Python, experience with Jupyter notebooks, and Python packages like polars, pandas, numpy, scikit-learn, matplotlib, etc. Experience with ML lifecycle: data preparation, training, evaluation, and deployment Hands-on experience with GCP services for ML & data science Experience with Vector Search and Hybrid Search techniques Embeddings generation using BERT, Sentence Transformers, or custom models Embedding indexing and retrieval (Elastic, FAISS, ScaNN, Annoy) Experience with LLMs and use cases like RAG Understanding of semantic vs lexical search paradigms Experience with Learning to Rank (LTR) and libraries like XGBoost, LightGBM with LTR support Proficient in SQL and BigQuery Experience with Dataproc clusters for distributed data processing using Apache Spark or PySpark Model deployment using Vertex AI, Cloud Run, or Cloud Functions Familiarity with BM25 ranking (Elasticsearch or OpenSearch) and vector blending Awareness of search relevance evaluation metrics (precision@k, recall, nDCG, MRR) Life at Next: At our core, we're driven by the mission of tailoring growth for our customers by enabling them to transform their aspirations into tangible outcomes. We're dedicated to empowering them to shape their futures and achieve ambitious goals. To fulfil this commitment, we foster a culture defined by agility, innovation, and an unwavering commitment to progress. Our organizational framework is both streamlined and vibrant, characterized by a hands-on leadership style that prioritizes results and fosters growth. Perks of working with us: Clear objectives to ensure alignment with our mission, fostering your meaningful contribution. Abundant opportunities for engagement with customers, product managers, and leadership. You'll be guided by progressive paths while receiving insightful guidance from managers through ongoing feedforward sessions. Cultivate and leverage robust connections within diverse communities of interest. Choose your mentor to navigate your current endeavors and steer your future trajectory. Embrace continuous learning and upskilling opportunities through Nexversity. Enjoy the flexibility to explore various functions, develop new skills, and adapt to emerging technologies. Embrace a hybrid work model promoting work-life balance. Access comprehensive family health insurance coverage, prioritizing the well-being of your loved ones. Embark on accelerated career paths to actualize your professional aspirations. Who we are? We enable high growth enterprises build hyper personalized solutions to transform their vision into reality. With a keen eye for detail, we apply creativity, embrace new technology and harness the power of data and AI to co-create solutions tailored made to meet unique needs for our customers. Join our passionate team and tailor your growth with us!

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Greetings From Mind Pro Technologies Pvt ltd (www.mindprotech.com) Job Title : Data Scientist Work Location : Karur (Tamil Nadu) or Dharwad (Karnataka ) Np : 15days or Less JOB DESCRIPTION: Must have At least 4+ Years of experience in Python with Data Science. Must have worked on at least one Live project. Experience in relevant field such as Statistics, Computer Science or Applied Math or Operational Research. Must have Masters in (Maths/Statistics or Applied Mathematics/Machine Learning etc.) History of successfully performing customer implementations Strong customer facing skills, and previous consulting experience. Experience of handling high frequency streaming data for real time analysis and reporting. Familiarity with - Natural Language Processing, Statistical Analysis (distribution analysis, correlation, variance, deep learning. Experience in tools like AWS, IBM Watson is a plus. Experience with open source technologies is a must. Excellent communication Ability to lead & build strong teams Ability to work in an ambiguous environment Desired Skills and Experience Languages/Tools: Python/R. Approaches: Machine Learning Concepts: Supervised ANN, Bayesian, Gaussian, Vector Quantization, Logistic Model, Statistical, Predictive Modeling, Minimum Message Length, SVM, Random Forest, Ensembles, ANOVA, Decision Trees, Hidden Markov Models Unsupervised ANN, ARL, Clustering Hierarchical, Cluster Analysis Reinforcement Gen AI, LLM, LSTM, RNN, CNN, KNN Big Data (Good to have): Hadoop /Kafka / Storm / Spark streaming OS: Linux, Windows 32/64 bits. Note: should know supervised and unsupervised learning, semi-supervised learning, neural networks concepts, and how ML algorithms works with training and testing data. Experience on particular data set to train, test and roll-out for production use Tool sets : Python, R, MATLAB or any AI frame work, Neural network, Gen AI, LLM Contact Details: Recruitment Team Mindpro Technologies Pvt Ltd ( www.mindprotech.com ) +91-04324-240904 / +91-9600672304

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Job Summary Should have worked hands-on in setting up ML services on public cloud and delivering ML based solutions. Should have 7 to 10 years of experience in AI ML and at least 1 year in GenAI leveraging cloud based GenAI services. Should have through knowledge of end-to-end deployment of GenAI solutions to customers cutting across the industry prevalence of GenAI. Responsibilities Key Responsibilities Research and Development Stay updated on generative AI advancements and methodologies conducting research to explore new techniques and experimenting with cutting-edge frameworks and libraries. Architecture Design Design tailored generative AI systems for specific applications developing scalable architectures leveraging cloud infrastructure and balancing model complexity with practical deployment considerations. Model Development and Training Develop custom generative models using deep learning frameworks training models on large-scale datasets with advanced optimization techniques and fine-tuning parameters to optimize performance metrics. Performance Evaluation and Optimization Evaluate model performance using quantitative and qualitative metrics identifying areas for improvement and optimizing model architectures to ensure efficiency and effectiveness of generative AI solutions. Integration and Deployment Integrate generative AI models into existing systems and applications developing APIs and interfaces for seamless interaction with other components and ensuring compatibility scalability and reliability in production environments. Collaboration and Communication Collaborate with cross-functional teams to understand requirements effectively communicate technical concepts to stakeholders and provide guidance and mentorship to junior team members. Technical Expertise Should have worked hands on in setting up ML services on public cloud and delivering ML based solutions. Should have 3 to 5 years of experience in AI ML and at least 1 year in GenAI leveraging cloud based GenAI services. Should have through knowledge of end-to-end deployment of GenAI solutions to customers cutting across the industry prevalence of GenAI. Should have handson experience in prompt engineering maintaining prompt libraries managing GenAI delivered code filtering avoiding duplicates etc. Should have created large scale PoVs or PoCs and presented to senior client teams. Should be able to define GenAI adoption roadmap for client industries based on their Enterprise needs. #LI-LK1

We are looking for a passionate and motivated AI Developer Fresher to join our growing AI team. This role will focus on Generative AI (GenAI) technologies such as large language models (LLMs), diffusion models, and other cutting-edge machine learning techniques. As a fresher, youll work closely with senior AI engineers and data scientists to build and fine-tune generative models, contribute to prompt engineering, and support model integration into real-world applications. Work Location: Chennai Mode of Employment: Initially hired as an Intern for a period of 6 months (Stipend: 15,000 per month) Full-Time employment will be offered post successful completion of internship (CTC: 5 LPA + Benefits) Eligibility Criteria: Education: B.E./B.Tech (AI/ML, AI/DS) Graduation Year: 2025 pass-outs only Technical Skills: GEN AI, Python Other Requirements: Must be willing to work from office (Chennai - SIPCOT IT Park, Siruseri) Should be ready to sign a service agreement/bond for 2 years and 6 months (including internship period) Must complete graduation in the academic year 2025 with no standing arrears Candidates must be from the local region (Chennai, TN location)

Job Overview: We are looking for a skilled Python and Data Science Programmer to develop and implement data-driven solutions. The ideal candidate should have strong expertise in Python, machine learning, data analysis, and statistical modeling. Key Responsibilities: Data Analysis & Processing: Collect, clean, and preprocess large datasets for analysis. Machine Learning: Build, train, and optimize machine learning models for predictive analytics. Algorithm Development: Implement data science algorithms and statistical models for problem-solving. Automation & Scripting: Develop Python scripts and automation tools for data processing and reporting. Data Visualization: Create dashboards and visual reports using Matplotlib, Seaborn, Plotly, or Power BI/Tableau. Database Management: Work with SQL and NoSQL databases for data retrieval and storage. Collaboration: Work with cross-functional teams, including data engineers, business analysts, and software developers. Research & Innovation: Stay updated with the latest trends in AI, ML, and data science to improve existing models.

Job Title: Data & GenAI AWS Specialist Experience: 1-4 Years Location: Bangalore Mandatory Qualification: B.E./ B.Tech/ M.Tech/ MS from IIT or IISc ONLY Job Overview: We are seeking a seasoned Data & GenAI Specialist with deep expertise in AWS Managed Services (PaaS) to join our innovative team. The ideal candidate will have extensive experience in designing sophisticated, scalable architectures for data pipelines and Generative AI (GenAI) solutions leveraging cloud services. Key to this role is the ability to articulate architecture solutions clearly and effectively to customers, helping them conceptualize and implement advanced GenAI-driven applications tailored precisely to their business requirements. Responsibilities: Engage closely with customers to thoroughly understand their business challenges, translate their requirements into comprehensive architecture solutions, and effectively communicate intricate technical details. Architect and oversee the design, development, and deployment of scalable, resilient data processing pipelines utilizing AWS/ Azure/ GCP/ Snowflake/ open Source services. Lead the architectural design and implementation of robust GenAI systems, leveraging AWS foundational models and frameworks including Amazon Bedrock, AWS Inferentia, Amazon SageMaker, and Amazon Kendra. Collaborate with internal and customer teams to align architectural strategies with business objectives, ensuring adherence to AWS best practices. Optimize and refine data architectures to effectively handle large-scale GenAI workloads, prioritizing performance, scalability, and robust security. Document and promote architectural best practices in data engineering, pipeline architecture, and GenAI development within AWS environments. Stay abreast of emerging architectural trends, innovative technologies, and advancements in AWS and GenAI ecosystems to ensure solutions remain cutting-edge and efficient. Have a keen sense of maximising and extending the AWS investments already done by the clients, instead of a rip and replace mentality. Qualifications: B.Tech/ MS/ M.Tech degree in Computer Science, Data Science, AI, or related technical fields Knowledge of architecting and building data pipelines and GenAI solutions specifically on AWS. Expert-level proficiency in AWS architectural patterns and services, including AWS Glue, Lambda, EMR, S3, and SageMaker. Why Join Us: Be at the forefront of cutting-edge GenAI and AWS cloud architectural innovation, working on the AI Lab. Thrive in a collaborative, dynamic, and supportive team environment. Continuous learning and growth opportunities.

Must have skills : - 6+ Years of Experience. - Statics, SQL, Big query, LLM, AI, Python - Work experience in the payments, ecommerce, or financial services industry is a plus . Responsibilities : - At least 6 years of experience analyzing large, multi-dimensional data sets and synthesizing insights into actionable solutions - Bachelor's/Master's degree in a quantitative field (such as Analytics, Statistics, Mathematics, Economics or Engineering) or equivalent field experience - Advanced SQL experience, preferable with Big Query analytics (Google Cloud) on Jupyter Notebooks and experience analyzing very large, complex, multi-dimensional data sets. - Understanding of statistics (e.g hypothesis testing, statistical inference, regression) and experience designing and evaluating complex experiments- - Ability to solve problems analytically and create actionable recommendations - Advanced ability to use reporting tools like Tableau and/or Excel to share analysis - Strong written and verbal communication skills with the ability to translate complex problems into simpler terms, expertise in stitching together findings to convey coherent insights and effectively influence both peers and senior leadership - Prior work experience in a product analytics space would be highly valued - A passion for problem-solving and comfort with ambiguity - Work experience in the payments, ecommerce, or financial services industry is a plus.

Responsibilities: Analysis of cross-customer and customer specific data. Analysis for diagnosis of product and customers specific problems and also to demonstrate value of our data to customers. Support sales and product adoption for data related use-cases (occupancy, captive portal, behavioral metrics, BMS integrations etc) Help design monitoring tools to detect product and customer relative issues around product Customer demonstrations of more sophisticated data products like Firehose. Engineering/Product linkages Collaborate with specialist teams to help deliver solutions. (Webex, Meraki etc) Leverage on ML based approaches for fault detection tools, for trends and also customer/category analysis Qualifications: Advanced degree or equivalent experience in Engineering, Computer Science, Maths or a related technical field Proficiency in programming and scripting languages R and/or Python Experience using relational database - SQL Basic proficiency with Machine Learning methods and applications Skills: Passion for problem solving. Highly driven and customer oriented. Excellent communication.

About the Role: We are seeking a highly skilled and innovative AI/ML Engineer with a strong background in Generative AI (LLMs, RAG, Multimodal models, Agentic AI) , core Machine Learning (including Deep Learning, NLP, and Vision), and hands-on experience with Data Visualization tools like Tableau . The ideal candidate should also be familiar with deploying solutions on cloud platforms, particularly AWS . Key Responsibilities: Design, develop, and fine-tune Large Language Models (LLMs) for diverse use cases using prompt engineering, fine-tuning, and embeddings. Implement Retrieval-Augmented Generation (RAG) pipelines with semantic search and vector databases (e.g., FAISS, Pinecone). Work on multimodal AI models involving text, image, and audio data for advanced AI capabilities. Build agentic AI systems using frameworks like LangChain, OpenAgents, or similar libraries. Develop, train, and evaluate Machine Learning /Deep Learning models for NLP and Computer Vision (object detection, OCR, etc.). Create insightful data dashboards and visualizations using Tableau to support business decision-making. Deploy ML pipelines and models on AWS cloud services (e.g., S3, SageMaker, Airflow, Glue). Familiarity with Microsoft Azure especially for OpenAI Collaborate with cross-functional teams to understand business problems and translate them into AI/ML solutions. Keep up-to-date with the latest advancements in Gen-AI, open-source tools, and cloud technologies. Preferred Qualifications: Bachelors or Masters in Computer Science, Data Science, or related field Required Skills: Gen-AI & LLMs: Experience with OpenAI, HuggingFace Transformers, LangChain, LlamaIndex, RAG architectures Experience in LLM evaluation, prompt optimization , fine-tuning/customizing base models Familiarity with agentic workflows , function calling, and orchestration tools Machine Learning: Strong fundamentals in deep learning, NLP, and computer vision Experience with TensorFlow, PyTorch, Scikit-learn Good grasp of model deployment, monitoring, and evaluation metrics Visualization & Storytelling: Proficient in Tableau for data visualization, dashboards, and storytelling with data Cloud & DevOps: Familiarity with AWS services (S3, Lambda, SageMaker, Glue , MWAA) Comfortable with Bitbucket (Git ) and CI/CD pipelines

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Develop algorithms that apply deep learning and innovative methods in NLP & computer vision, combined with traditional large sophisticated solutions/codebases! Developing innovative solutions using Generative AI, Python, Machine Learning and Data Science! Build experiments, algorithms and ship solution that not only yield high accuracy but are also crafted and engineered to scale. Collaborate across multiple research and engineering teams, making the tradeoffs required to rapidly deliver AI/ML software solutions. Driven, Energetic and a team player are must haves.

A key enabler of our services is leveraging data in delivering client solutions. The data available about customers is getting richer and the problems that our customers are trying to answer continue to evolve. In our endeavor to stay ahead in providing solutions to these evolving complex problems, ZS has set up an Advanced Data Science which has three major focus areas: Research the evolving datasets and advanced analytical techniques to develop new offerings/solutions Deliver client impact by collaboratively implementing these solutions Provide thought leadership by developing the ZS Point of View in this space Data Science Managers (DSMs) design, develop and execute analytic techniques on large, complex, structured and unstructured data sets (including big data) to help clients make better fact-based decisions. DSMs will develop new offerings/solutions, drive client impact by delivering client solutions and shape the ZS point of view in this space. You will be responsible for applying analytical techniques to model complex business problems, uncovering insights, and identifying opportunities using statistical, algorithmic, mining, and visualization techniques. What you'll Do: Lead and mentor a team of data scientists, providing guidance and support to ensure the successful execution of client projects. Develop and implement data science strategies that align with the overall goals of the AI team and the organization. Drive business and strategy development through project delivery and client relationship management; Develop/sell new business opportunities Direct multiple projects simultaneously, honing analytic and project management skills; Play a key role in development of data science capabilities and offerings that create scale and advance our analytic platform; Motivate, coach and serve as a role model for project team members Provide thought leadership and innovation through research and publication. What you'll Bring: PhD degree in Computer Science, Statistics or related discipline; 8+ years of relevant post-collegiate work experience; in lieu of a PhD, 10+ years of work experience may substitute. Experience with big data, claims analytics, advanced analytics concepts and algorithms (eg text mining, social listening, recommender systems, predictive modeling, Gen AI, proficiency with large language models etc); Relevant programming background (eg Python/R); Strong understanding of relevant tools/platforms (eg cloud platforms such AWS/Azure); Proven track record of business development Agile project planning and project management experience; Team management and skill development experience; Relevant domain knowledge preferred; (healthcare, pharma); Excellent oral and written communication skills; Strong attention to detail, with a research-focused mindset; Excellent critical thinking and problem solving skills;