206 Time Series Jobs - Page 8

Job description: Enable data driven decision making across the Tesco business globally by developing analytics solutions using a combination of math, tech and business knowledge. In this job, I am accountable for: Following our Business Code of Conduct and always acting with integrity and due diligence and have these specific risk responsibilities: - Understands business needs and in depth understanding of Tesco processes - Builds on Tesco processes and knowledge by applying CI tools and techniques. - Responsible for completing tasks and transactions within agreed KPI's - Solves problems by analyzing solution alternatives Engaging with business & functional partners to understand business priorities, ask relevant questions and scope same into a analytical solution document calling out how application of data science will improve decision making In depth understanding of techniques to prepare the analytical data set leveraging multiple complex data set sources - Building Statistical models and ML algorithms with practitioner level competency -Writing structured, modularized & codified algorithms using Continuous Improvement principles (development of knowledge assets and reusable modules on GitHub, Wiki, etc) with expert competency - Building easy visualization layer on top of the algorithms in order to empower end-users to take decisions - this could be on a visualization platform (Tableau / Python) or through a recommendation set through PPTs Working with the line manager to ensure application / consumption and proactively identifying opportunities to help the larger Tesco business with areas of improvement. Experience relevant for this job: - Applied Math: Applied Statistics, Design of Experiments, - 2 - 4 years experience in data science application in Retail or Regression, Decision Trees, Forecasting, Optimization CPG Preferred algorithms, Clustering, NLP - Functional experience: Marketing, Supply Chain, Customer, - Tech: SQL, Hadoop, Spark, Python, Tableau, MS Excel, MS Merchandising, Operations, Finance or Digital PowerPoint, GitHub - Business: Basic understanding of Retail domain - Soft Skills: Analytical Thinking & Problem solving, Storyboarding, Articulate communication

Preferred skills and qualifications 7 or more years of experience in building and delivering analytical applications.BE/BTech or higher degree in Computer Science, Computer Engineering.Excellent knowledge on OBIEE/OAC RPD development.Experience in OBIEE/OAC Reports & Dashboard and/or Data Visualization Projects development.Exposure to Data Warehouse design, Star Schema modeling. Career Level - IC3 Responsibilities Build and manage the OAC RPD models to optimize data accessibility and performance.Create dynamic, user-friendly OAC dashboards and visualizations that turn data into insights.Set up alerts and automate data flows to keep business teams informed in real-time. Collaborate on data warehouse design, data pipelines, helping shape how we store and manage data.Use ETL tools (Oracle Data Integrator) to move and transform data, ensuring its ready for analysis.Have a good broader business understanding and mindset, while technically leading efforts in specific areas. Make effective judgments and choices on design and roadmap based on various considerations.Work with business and technical teams to understand needs and deliver effective OAC solutions.Troubleshoot and solve any issues that come up with data flows, dashboards, or OAC configurations. Stay current with OAC updates and best practices, continually improving our analytics capabilities.Excellent knowledge in development of repository at all the three layers including Physical Layer, Business Model and Mapping Layer and Presentation Layer.Knowledge in creating Logical columns, Hierarchies (Level Based, Parent Child), Measures, Aggregation Rules,Aggregations, Time Series in Business Model and Catalog Folders in Presentation layers. Good Knowledge in security set up for reports and dashboards, and OBIEE administrative activities.Experience on Oracle SQL, database performance tuning by implementing Views, Materialized views, creating indexes.Strong interpersonal and team leadership skills

Preferred skills and qualifications 7 or more years of experience in building and delivering analytical applications.BE/BTech or higher degree in Computer Science, Computer Engineering.Excellent knowledge on OBIEE/OAC RPD development.Experience in OBIEE/OAC Reports & Dashboard and/or Data Visualization Projects development.Exposure to Data Warehouse design, Star Schema modeling. Career Level - IC3 Responsibilities Build and manage the OAC RPD models to optimize data accessibility and performance.Create dynamic, user-friendly OAC dashboards and visualizations that turn data into insights.Set up alerts and automate data flows to keep business teams informed in real-time.Collaborate on data warehouse design, data pipelines, helping shape how we store and manage data.Use ETL tools (Oracle Data Integrator) to move and transform data, ensuring its ready for analysis. Have a good broader business understanding and mindset, while technically leading efforts in specific areas.Make effective judgments and choices on design and roadmap based on various considerations.Work with business and technical teams to understand needs and deliver effective OAC solutions.Troubleshoot and solve any issues that come up with data flows, dashboards, or OAC configurations. Stay current with OAC updates and best practices, continually improving our analytics capabilities.Excellent knowledge in development of repository at all the three layers including Physical Layer, Business Model and Mapping Layer and Presentation Layer. Knowledge in creating Logical columns, Hierarchies (Level Based, Parent Child), Measures, Aggregation Rules,Aggregations, Time Series in Business Model and Catalog Folders in Presentation layers. Good Knowledge in security set up for reports and dashboards, and OBIEE administrative activities.Experience on Oracle SQL, database performance tuning by implementing Views, Materialized views, creating indexes.Strong interpersonal and team leadership skills

Role & responsibilities Data scientist with strong Python development skills and strong Natural Language Processing experience ideally including Topic Modelling. Experience of developing LLM-based Generative AI applications including prompt engineering and use of LLM orchestration frameworks (e.g. Lanchain and/or Llama-index). Ideal candidates will have experience in Life Sciences & Healthcare. Core Skills Data Science Python Natural Language Processing Generative AI Additional Preferred Skills Topic Modelling / BERTopic LLM Orchestration Frameworks (Langchain / llama-index / HuggingFace) LLM Application Development AI Ethics / Responsible AI

Role & responsibilities Data scientist with strong Python development skills and strong Natural Language Processing experience ideally including Topic Modelling. Experience of developing LLM-based Generative AI applications including prompt engineering and use of LLM orchestration frameworks (e.g. Lanchain and/or Llama-index). Ideal candidates will have experience in Life Sciences & Healthcare. Core Skills Data Science Python Natural Language Processing Generative AI Additional Preferred Skills Topic Modelling / BERTopic LLM Orchestration Frameworks (Langchain / llama-index / HuggingFace) LLM Application Development AI Ethics / Responsible AI

Were Hiring: Data Scientist – Supply Chain Analytics Location: Hyderabad, India – Hybrid (3 Days WFO / 2 Days WFH) Full-Time | Permanent Position Experience: 2–5 Years Company: Solenis GSS India About the Role Solenis GSS India is looking for a Data Scientist to join our Supply Chain Analytics team. If you have strong expertise in SQL, Python, Advanced Excel, and Machine Learning, this is your chance to work on impactful global projects and help drive data-based decision-making. What You’ll Do Develop & maintain reports and analytical solutions. Translate business requirements into data-driven insights. Work on large datasets for cleaning, processing, and analysis. Build & evaluate machine learning models for forecasting & optimization. Apply statistical models (correlation, regression, time series forecasting). Collaborate with cross-functional teams and manage small projects. Must-Have Skills SQL – Advanced queries, large dataset handling, schedulers. Python – NumPy, Pandas, Scikit-learn. Advanced Excel – Pivot Tables, VLOOKUP, advanced formulas. Machine Learning & Statistics – Regression, classification, time series. Good to Have Skills Snowflake Qualifications Bachelor’s/Master’s degree in Data Science, Statistics, Computer Science, or related field. 2–5 years of hands-on experience in data science or analytics. Apply now and be part of a global leader in sustainable solutions! Interested in this role? Send your resume to PNandanavanam@Solenis.com

Bachelors/Master’s degree in Computer Science, Data Science, AI/ML, or related field. Strong programming experience in Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow). Solid experience in machine learning, NLP, and deep learning frameworks . Hands-on expertise in LLMs (OpenAI, Hugging Face Transformers, LangChain, RAG frameworks) . Knowledge of vector databases (Pinecone, Weaviate, FAISS, Milvus) for semantic search and retrieval-augmented generation. Experience with cloud AI services (AWS SageMaker, GCP Vertex AI, Azure ML). Strong skills in SQL and data visualization tools (Power BI, Tableau, or similar). Familiarity with MLOps and model lifecycle management . Excellent analytical, problem-solving, and stakeholder communication skills. Good to Have (Preferred): Experience with multi-modal LLMs (text + image, text + speech). Understanding of Reinforcement Learning from Human Feedback (RLHF) . Contributions to open-source NLP/LLM projects. Prior experience in financial services, healthcare, or e-commerce domain is a plus.

Title: AI/ML Architect Location: Onsite Bangalore Experience: 10+ years Position Summary: We are seeking an experienced AI/ML Architect to lead the design and deployment of scalable AI solutions. This role requires a strong blend of technical depth, systems thinking, and leadership in machine learning , computer vision , and real-time analytics . You will drive the architecture for edge, on-prem, and cloud-based AI systems, integrating 3rd party data sources, sensor and vision data to enable predictive, prescriptive, and autonomous operations across industrial environments. Key Responsibilities: Architecture & Strategy Define the end-to-end architecture for AI/ML systems including time series forecasting , computer vision , and real-time classification . Design scalable ML pipelines (training, validation, deployment, retraining) using MLOps best practices. Architect hybrid deployment models supporting both cloud and edge inference for low-latency processing. Model Integration Guide the integration of ML models into the IIoT platform for real-time insights, alerting, and decision support. Support model fusion strategies combining disparate data sources, sensor streams with visual data (e.g., object detection + telemetry + 3rd party data ingestion). MLOps & Engineering Define and implement ML lifecycle tooling, including version control, CI/CD, experiment tracking, and drift detection. Ensure compliance, security, and auditability of deployed ML models. Collaboration & Leadership Collaborate with Data Scientists, ML Engineers, DevOps, Platform, and Product teams to align AI efforts with business goals. Mentor engineering and data teams in AI system design, optimization, and deployment strategies. Stay ahead of AI research and industrial best practices; evaluate and recommend emerging technologies (e.g., LLMs, vision transformers, foundation models). Must-Have Qualifications: Bachelor’s or Master’s degree in Computer Science, AI/ML, Engineering, or a related technical field. 8+ years of experience in AI/ML development, with 3+ years in architecting AI solutions at scale. Deep understanding of ML frameworks (TensorFlow, PyTorch), time series modeling, and computer vision. Proven experience with object detection, facial recognition, intrusion detection , and anomaly detection in video or sensor environments. Experience in MLOps (MLflow, TFX, Kubeflow, SageMaker, etc.) and model deployment on Kubernetes/Docker . Proficiency in edge AI (Jetson, Coral TPU, OpenVINO) and cloud platforms (AWS, Azure, GCP). Nice-to-Have Skills: Knowledge of stream processing (Kafka, Spark Streaming, Flink). Familiarity with OT systems and IIoT protocols (MQTT, OPC-UA). Understanding of regulatory and safety compliance in AI/vision for industrial settings. Experience with charts, dashboards, and integrating AI with front-end systems (e.g., alerts, maps, command center UIs). Role Impact: As AI/ML Architect, you will shape the intelligence layer of our IIoT platform — enabling smarter, safer, and more efficient industrial operations through AI. You will bridge research and real-world impact , ensuring our AI stack is scalable, explainable, and production-grade from day one. ]

Entity :- Accenture Strategy & Consulting Job location :- Mumbai About S&C - Global Network :- Accenture Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition WHATS IN IT FOR YOU Accenture CFO & EV team under Data & AI team has comprehensive suite of capabilities in Risk, Fraud, Financial crime, and Finance. Within risk realm, our focus revolves around the model development, model validation, and auditing of models. Additionally, our work extends to ongoing performance evaluation, vigilant monitoring, meticulous governance, and thorough documentation of models. Get to work with top financial clients globally Access resources enabling you to utilize cutting-edge technologies, fostering innovation with the worlds most recognizable companies. Accenture will continually invest in your learning and growth and will support you in expanding your knowledge. Youll be part of a diverse and vibrant team collaborating with talented individuals from various backgrounds and disciplines continually pushing the boundaries of business capabilities, fostering an environment of innovation. What you would do in this role Engagement Execution Work independently/with minimal supervision in client engagements that may involve model development, validation, governance, strategy, transformation, implementation and end-to-end delivery of risk solutions for Accentures clients. Ability to manage workstream of large projects / small projects with responsibilities of managing quality of deliverables for junior team members. Demonstrated ability of managing day to day interactions with the Client stakeholders Practice Enablement Guide junior team members. Support development of the Practice by driving innovations, initiatives. Develop thought capital and disseminate information around current and emerging trends in Risk. Qualification Who we are looking for 7 - 12 years of relevant Risk Analytics experience at one or more Financial Services firms, or Professional Services / Risk Advisory with significant exposure to one or more of the following areas: Development, validation, and audit of: Credit Risk- PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting and Revenue Forecasting Models, IFRS9/CECL Loss Forecasting Models across Retail and Commercial portfolios Credit Acquisition/Behavior/Collections/Recovery Modeling and Strategies, Credit Policies, Limit Management, Acquisition Frauds, Collections Agent Matching/Channel Allocations across Retail and Commercial portfolios Regulatory Capital and Economic Capital Models Liquidity Risk Liquidity models, stress testing models, Basel Liquidity reporting standards Anti Money Laundering AML scenarios/alerts, Network Analysis Operational risk AMA modeling, operational risk reporting Conceptual understanding of Basel/CCAR/DFAST/CECL/IFRS9 and other risk regulations Experience in conceptualizing and creating risk reporting and dashboarding solutions. Experience in modeling with statistical techniques such as linear regression, logistic regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time series ARMA/ARIMA, ML interpretability and bias algorithms etc. Programing Languages - SAS, R, Python, Spark, Scala etc., Tools such as Tableau, QlikView, PowerBI, SAS VA etc. Strong understanding of Risk function and ability to apply them in client discussions and project implementation. Academic : Masters degree in a quantitative discipline mathematics, statistics, economics, financial engineering, operations research or related field or MBA from top-tier universities. Strong academic credentials and publications, if applicable. Industry certifications such as FRM, PRM, CFA preferred. Excellent communication and interpersonal skills. Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.

About Zscaler Serving thousands of enterprise customers around the world including 45% of Fortune 500 companies, Zscaler (NASDAQ: ZS) was founded in 2007 with a mission to make the cloud a safe place to do business and a more enjoyable experience for enterprise users. As the operator of the world’s largest security cloud, Zscaler accelerates digital transformation so enterprises can be more agile, efficient, resilient, and secure. The pioneering, AI-powered Zscaler Zero Trust Exchange™ platform, which is found in our SASE and SSE offerings, protects thousands of enterprise customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Named a Best Workplace in Technology by Fortune and others, Zscaler fosters an inclusive and supportive culture that is home to some of the brightest minds in the industry. If you thrive in an environment that is fast-paced and collaborative, and you are passionate about building and innovating for the greater good, come make your next move with Zscaler. Our Engineering team built the world's largest cloud security platform from the ground up, and we keep building. With more than 100 patents and big plans for enhancing services and increasing our global footprint, the team has made us and our multitenant architecture today's cloud security leader, with more than 15 million users in 185 countries. Bring your vision and passion to our team of cloud architects, software engineers, security experts, and more who are enabling organizations worldwide to harness speed and agility with a cloud-first strategy. We're looking for an experienced Staff Machine Learning Software Engineer to join our digital experience team . Reporting to the Director, you'll be responsible for: Leading identification and resolution of performance issues by developing advanced AI/ML models that pinpoint root causes of poor experience and detect performance bottlenecks for users Developing, maintaining, and refining predictive models to forecast user behavior, system performance, and potential friction points in the digital experience Implementing advanced AI/ML algorithms to detect and forecast anomalies in user experience across multiple dimensions Overseeing the entire lifecycle of ML projects, including analysis, training, testing, building, and deploying ML models into production environments Designing and creating compelling visualizations to effectively communicate findings and insights to both technical and non-technical stakeholders What We're Looking for (Minimum Qualifications) A Bachelors or Master’s(preferable) degree in Computer Science, Data Science, Statistics, or a related field with 6+ years of professional experience in data science or a related role Proficiency with data science tools and platforms such as Python, R, TensorFlow, SQL, and related libraries and frameworks Strong experience with networking and end-point observability systems Expertise in multi-dimensional anomaly detection algorithms, with a specific focus on time series data sets Strong experience in building and deploying ML models in production environments, including model orchestration using tools like Kubernetes and Airflow What Will Make You Stand Out (Preferred Qualifications) Published research or contributions to digital experience/end-user observability/networking/ data science community Demonstrated experience in the monitoring space, with a deep understanding of user experience metrics, monitoring tools, and methodologies Experience with designing complex systems and scaling ML models on large scale distributed systems #LI-Hybrid #LI-AN4 At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure. Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including: Various health plans Time off plans for vacation and sick time Parental leave options Retirement options Education reimbursement In-office perks, and more! Learn more about Zscaler’s Future of Work strategy, hybrid working model, and benefits here. By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines. Zscaler is committed to providing equal employment opportunities to all individuals. We strive to create a workplace where employees are treated with respect and have the chance to succeed. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status, or any other characteristic protected by federal, state, or local laws. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link. Pay Transparency Zscaler complies with all applicable federal, state, and local pay transparency rules. Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.

Role: Gather relevant information to define the business problem Creative thinker capable of linking AI methodologies to identified business challenges Develop AI/ML applications leveraging the latest industry and academic advancements Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You: Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks Feedforward, CNN, LSTMs GRUs is a plus. Optimization techniques Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Concentration in Computer Science.

About the Role We are seeking a Data Scientist with strong expertise in Python and SQL to join our growing data team. Youll work on data modeling, predictive analytics, and business intelligence projects that directly impact strategic decision-making. Key Responsibilities Extract, clean, and transform data from multiple sources using SQL and Python. Build predictive models and machine learning algorithms for business use cases. Perform exploratory data analysis (EDA) and generate actionable insights. Create interactive dashboards & reports (Power BI/Tableau). Optimize and maintain data pipelines, ETL processes, and workflows . Collaborate with cross-functional teams to translate business needs into analytical solutions. Present analytical results in a clear, visual, and business-friendly format. Required Skills 1–5 years of experience in Data Science or Data Analytics roles. Strong proficiency in Python (NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn). Advanced SQL skills (complex queries, joins, window functions, optimization). Understanding of machine learning algorithms and statistical methods. Experience in data visualization tools (Power BI, Tableau, or similar). Strong problem-solving and analytical skills. Bachelor’s/Master’s in Computer Science, Data Science, Statistics, Mathematics, or related fields. Nice to Have Familiarity with cloud platforms (AWS, Azure, GCP). Exposure to Big Data tools (Spark, Hadoop). Basic understanding of APIs and automation scripts . What We Offer Competitive industry-standard salary + performance incentives. Flexible working hours & hybrid/remote opportunities. Exposure to real-world, high-impact projects .

About the Role: We are looking for a motivated Junior AI/ML Engineer with a strong foundation in NLP, SQL, Python, machine learning, and deep learning. The ideal candidate will have hands-on experience implementing ML algorithms, integrating models via APIs, working with Generative AI, and coding in both Python and C for performance-critical tasks. Key Responsibilities: Develop, train, and optimize ML/DL models for various business use cases. Build NLP pipelines for text classification, sentiment analysis, entity recognition, and conversational AI. Implement and fine-tune Generative AI models (LLMs, diffusion models) for innovative solutions. Apply core ML algorithms (regression, classification, clustering, recommendation, etc.) to solve problems. Write efficient code in Python for data preprocessing, feature engineering, and model training. Utilize C for performance optimization in computationally heavy components. Integrate models into production systems through RESTful APIs. Extract, manipulate, and analyze structured and unstructured data using SQL . Collaborate with cross-functional teams to gather requirements and deliver solutions. Stay up to date with emerging trends in AI/ML, NLP, and Generative AI. Required Skills & Qualifications: Bachelors degree in Computer Science, AI, Data Science, or a related field. 3-5 years of relevant AI/ML experience. Strong programming skills in Python and proficiency in C . Solid knowledge of ML algorithms and practical implementation experience. Proficiency in SQL for database querying and data analysis. Hands-on experience with NLP tools/libraries (spaCy, NLTK, Hugging Face Transformers). Familiarity with ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn). Knowledge of Generative AI techniques and models (GPT, LLaMA, Stable Diffusion, etc.). Experience working with RESTful APIs for AI model deployment. Understanding of software engineering best practices (Git, code optimization, testing). Role & responsibilities Preferred candidate profile

Location - All Genpact Locations Responsibilities Professional experience with different regression and classification methods in implementation and deployment of project on AWS GCP and Azure cloud platform. Follow the standard practice and guidelines while using Python, SQL. Experience with Langchain framework for GenAI. Develop and fine-tuning Generative AI models such as GPT for various applications. Using Generative AI to work on tasks like text generation, sentiment analysis, chatbots and language translation using RAG and agent-based models. Adjust language models that have already been trained for generative AI applications. Experience in tokenization and embeddings and must have used GPT, LLaMA, Huggingface, Mistral, AWS BedRock for deploying the models. Analyze data and Generating insights using generative AI techniques for predictive modelling and data generation. Building chatbot using different scalable data source for generating charts and statement. Having experience building front end application using Streamlit/Gradio/Flask/Fast for Generative AI input and output display. Responsible for weekly release of upgrades and new features to enhance current algorithm. Evaluating the performance of generative AI models and implementing improvements based on feedback. Ensuring ethical and responsible use of AI by addressing bias, privacy concerns and fairness in AI models. Must Demonstrate understanding of evaluation metrics specific to GenAI task such as inception score, frechet inception distance, perpetual path length. Collaborating with cross-functional teams, including data scientist, engineers, and domain experts to integrate Generative AI into product or services. Able to design Machine learning, Deep learning and Generative AI architecture and its successful execution in the project. Must have basic understanding on Word and Excel. Proficiency in programming language like Python, SQL, frameworks such as Langchain for AI model development. Experience on Rest API, Flask API, Fast API. Qualifications we seek in you!Minimum Qualifications / Skills Any Graduate BE/B- Tech, BCA, MCA, BSc/MSc Behavioral / team skills Personal drive and positive work ethic to deliver results within tight deadlines and in demanding situations Flexibility to adapt to a variety of engagement types, working hours and work environments and locations Excellent written, oral communication and presentation skills Bring a data-driven approach to decision making intellectually curious, always eager to learn new skills and share the knowledge with others Proactive planner and can work independently to manage own responsibilities Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook.Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

Lead the medium to large scale unified operations project on Aveva System Platform as functional consultant preferably in oil and gas domain. Design and Architect Unified Operation centers. Develop and demonstrate relevant use cases as a presales.

Description: Note that this is an authentic "Data Analyst" role. Must Have skills/competencies 5 years hands-on experience with data analysis to extract inferences and trends from huge amounts of data using a variety of techniques for analyzing data to gain valuable insights that can enhance various aspects of business/operations.The data can be qualitative, quantitative and time series. including Exploratory data analysis Causal data analysis Statistical data analysis (descriptive and inferential) Regressions, correlation, experiments, hypothesis testing etc Some experience with data visualization tools like PowerBI or data visualization libraries (for example MatPlotLib, Seaborn etc.) 2 to 3 years strong hands on experience with writing complex SQL queries Ability to work with multiple stakeholders to understand the data, come-up with several options to analyse, slice & dice the data to bring out trends and action items for better business outcome. Good to have Hands-on experience with Python Understanding of no-SQL db Requirements: Note that this is an authentic "Data Analyst" role. Must Have skills/competencies 5 years hands-on experience with data analysis to extract inferences and trends from huge amounts of data using a variety of techniques for analyzing data to gain valuable insights that can enhance various aspects of business/operations.The data can be qualitative, quantitative and time series. including Exploratory data analysis Causal data analysis Statistical data analysis (descriptive and inferential) Regressions, correlation, experiments, hypothesis testing etc Some experience with data visualization tools like PowerBI or data visualization libraries (for example MatPlotLib, Seaborn etc.) 2 to 3 years strong hands on experience with writing complex SQL queries Ability to work with multiple stakeholders to understand the data, come-up with several options to analyse, slice & dice the data to bring out trends and action items for better business outcome. Good to have Hands-on experience with Python Understanding of no-SQL db Job Responsibilities: Note that this is an authentic "Data Analyst" role. Must Have skills/competencies 5 years hands-on experience with data analysis to extract inferences and trends from huge amounts of data using a variety of techniques for analyzing data to gain valuable insights that can enhance various aspects of business/operations.The data can be qualitative, quantitative and time series. including Exploratory data analysis Causal data analysis Statistical data analysis (descriptive and inferential) Regressions, correlation, experiments, hypothesis testing etc Some experience with data visualization tools like PowerBI or data visualization libraries (for example MatPlotLib, Seaborn etc.) 2 to 3 years strong hands on experience with writing complex SQL queries Ability to work with multiple stakeholders to understand the data, come-up with several options to analyse, slice & dice the data to bring out trends and action items for better business outcome. Good to have Hands-on experience with Python Understanding of no-SQL db What We Offer: Exciting Projects: We focus on industries like High-Tech, communication, media, healthcare, retail and telecom. Our customer list is full of fantastic global brands and leaders who love what we build for them. Collaborative Environment: You Can expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment — or even abroad in one of our global centers or client facilities! Work-Life Balance: GlobalLogic prioritizes work-life balance, which is why we offer flexible work schedules, opportunities to work from home, and paid time off and holidays. Professional Development: Our dedicated Learning & Development team regularly organizes Communication skills training(GL Vantage, Toast Master),Stress Management program, professional certifications, and technical and soft skill trainings. Excellent Benefits: We provide our employees with competitive salaries, family medical insurance, Group Term Life Insurance, Group Personal Accident Insurance , NPS(National Pension Scheme ), Periodic health awareness program, extended maternity leave, annual performance bonuses, and referral bonuses. Fun Perks: We want you to love where you work, which is why we host sports events, cultural activities, offer food on subsidies rates, Corporate parties. Our vibrant offices also include dedicated GL Zones, rooftop decks and GL Club where you can drink coffee or tea with your colleagues over a game of table and offer discounts for popular stores and restaurants!

Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Economics, Statistics, Data Science) Preferred Institution: NIT, ISI, Any - School of Economics Responsibilities: Serve as expert in Data Science, build framework to develop Production level DS/AI models. Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients. Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions. Present results, insights, and recommendations to senior management with an emphasis on the business impact. Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization. Required Skills: Expertise in ML - Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA, Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers. Expertise in programming languages SQL, Python/ R, Spark. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch). Experience with cloud computing services Azure. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing. Knowledge in Mathematical programming - Linear Programming, Mixed Integer Programming etc , Stochastic Modelling - Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models. Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP). Knowledge in GPU code optimization, Spark MLlib Optimization. Familiarity to deploy and monitor ML models in production, delivering data products to end-users. Experience with ML CI/CD pipelines.

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful. Overview about TII: At Target, we have a timeless purpose and a proven strategy. And that hasnt happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Targets global team and has more than 4,000 team members supporting the companys global strategy and operations. Pyramid overview: A role with Target Techs Data Science team means the chance to develop and manage state of the art machine learning algorithms that use data at scale to automate and optimize decisions. Whether you join our Statistics, Optimization or Machine Learning teams, youll be challenged to harness Targets impressive data breadth to build the algorithms that power solutions our partners in in Stores, Supply Chain Optimization, and Network Planning rely on. Every Scientist on Targets Data Sciences team can expect modelling and data science, software/product development of highly performant code for performance, and to elevate Targets culture and apply retail domain knowledge. Team Overview: Our Stores Data Science team oversees the development of state-of-the-art mathematical techniques to solve key problems for Targets Stores, such as identifying optimal tasks prioritizing work and sequence work for our teams to meet the dynamic guest demands. The team leverage machine learning, operations research and simulation to help design the future of how our stores work. Position Overview: As aLead Data Scientist, youll influence by interacting with the Data Sciences team, Product teams, Scientist/Engineer individual contributors from other pillars, and business partners. You will perform within the scope of your role by defining solutions and beginning to identify problems to solve. You will contribute to Data Sciences and Targets culture by modeling and contributing to the ways we work. There are several ways to use your expertise in one or more of the following areasmachine learning, probability theory & statistics, optimization theory, Simulation, Econometrics, and machine learning. We will look to you to own design and implementation of an algorithmic solution (e.g., predictions, optimization or simulations), including data understanding, feature engineering, model development, validation and testing, and deployment to a production environment. Youll drive development of problem statements that capture the business considerations, define metrics/measurement to validate model performance, and drive feasibility study with data requirements and potential solutions approaches to be considered. Youll evaluate trade-offs of simple vs complex models/solutions in determining the right technique to employ for a business problem and develop and maintain a nuanced understanding of the data generated by the business, including fundamental limitations of the data. Youll leverage your proficiency in one or more approved programming languages (Java, Scala, Python, R), and ensure foundational programming principles in developing code (best practices, writes unit tests, code organization, basics of CI/CD etc.) are followed in developing the teams products/models. Youll not only stitch together basic data pipelines for a given problem and own design and implementation of individual components within Data Science/Tech applications, but also articulate the technical strategy, value of technology, and impact on the business. As you do so, youll collaborate with engineers, scientists, and business partners/product owners to create algorithmic solutions that are performant and integrated into applications. Well look to you to mentor and provide technical support within a team, including mentoring junior team members, and present your work and your teams work to business partners and other Data Sciences teams. With a deeper understanding of your functional area of responsibility, youll support agile ceremonies, collaborate with peers across multiple products, communicate and collaborate with business partners, and demonstrate an understanding of areas outside your scope of responsibility. The exciting part of retailIts always changing! Core responsibilities of this job are described within this job description.Job duties may change at any time due to business needs. About You: 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) and 6+ years of professional experience or equivalent industry experience Masters degree in Quantitative disciplines (Science, Operations Research, Technology, Engineering, Mathematics) Good knowledge and experience developing optimization, simulation, and statistical models Strong analytical thinking skills. Ability to creatively solve business problems, innovating new approaches where required Strong hands-on programming skills in Python, SQL, Hadoop/Hive. Additional knowledge of Spark, Scala, R, Java desired but not mandatory Good working knowledge of mathematical and statistical concepts, MILP, algorithms, and computational complexity Passion for solving interesting and relevant real-world problems using a data science approach Experience in implementing advanced statistical techniques like regression, clustering, PCA, forecasting (time series) etc. Able to produce reasonable documents/narrative suggesting actionable insights Excellent communication skills. Ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives Self-driven and results oriented; able to meet tight timelines Strong team player with ability to collaborate effectively across geographies/time zones Know More About us here: Life at Target- https://india.target.com/ Benefits- https://india.target.com/life-at-target/workplace/benefits Culture- https://india.target.com/life-at-target/belonging

Job Role: Data scientists will develop and maintain statistical models, apply machine learning techniques and build high-quality predictive/prescriptive systems. The Sr data scientist will also make technology and business recommendations, as well as develop key insights based on data analysis. The candidate must be able to partner with business stakeholders in order to cure business problem statements and guide which business priorities using data. About NAM NAM Info Inc. a talent management organization specializes in IT Services delivery and Product development. Job Title: Data Scientist / Lead Data Scientist Company: NAM Info Private Limited Location: Bangalore (Work from Office all 5days a week) Experience: 8-12 Years Positions: 2 Data Scientists & 1 Lead Data Scientist Joining: Immediate joiners preferred (within 15 days) Interview Process: Round 1: Virtual Round 2: Face-to-face Academic Qualifications: Engineering / B Tech or Masters in Computer SCience Responsibilities: Strong knowledge and hands on experience in exploration data analysis (EDA) Require reasonable exposure to Retail domain. 2+yrs of experience in ML Model Experience where the candidate has built and deployed Machine learning models at scale Must have Comfortable in Python (Coding) and build the model understanding concept Experience in feature engineering: Experience in building derived variable and hyperparameter tuning Types of models experience expected: Classification models, Regression models, Clustering, Forecasting (Experience in Machine Learning and Deep Learning Techniques) Experience with Hadoop, Apache Spark, Kafka, and cloud platforms (AWS, GCP, Azure). Proficient with EC2, S3, RDS, Lambda, Snowflake, and big data technologies. Data Visualization and BI Tools: Created interactive dashboards and reports using Tableau, Power BI, and D3.js to facilitate data-driven decision-making. Must have worked on banking use cases like cross sell, upsell, customer retention, customer acquisition, customer servicing, personalization, ATM optimization, Branch analytics Expertise in data science mining and Time Series, modeling, deep learning, CNN, clustering, boosting, classification, predictive modeling, LSTM, and LLMs. Note: Apply only if you meet the Expectation criteria which mentioned in the Job Description. Send profiles to narasimha@nam-it.com Thanks & regards, Narasimha.B Staffing executive NAM Info Pvt Ltd, 29/2B-01, 1st Floor, K.R. Road, Banashankari 2nd Stage, Bangalore - 560070. +91 9182480146 (India) Email - narasimha@nam-it.com

Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Economics, Statistics, Data Science) Preferred Institution: NIT, ISI, Any - Scool of Economics Responsibilities: Serve as expert in Data Science, build framework to develop Production level DS/AI models. Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients. Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions. Present results, insights, and recommendations to senior management with an emphasis on the business impact. Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization. Required Skills: Expertise in ML - Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA, Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers. Expertise in programming languages SQL, Python/ R, Spark. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch). Experience with cloud computing services Azure. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing. Knowledge in Mathematical programming - Linear Programming, Mixed Integer Programming etc , Stochastic Modelling - Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models. Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP). Knowledge in GPU code optimization, Spark MLlib Optimization. Familiarity to deploy and monitor ML models in production, delivering data products to end-users. Experience with ML CI/CD pipelines.

Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Economics, Statistics, Data Science) Preferred Institution: NIT, ISI, Any - School of Economics Required Skills: Expertise in ML - Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA, Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers. Expertise in programming languages SQL, Python/ R, Spark. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch). Knowledge in cloud computing services Azure. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing. Knowledge in Mathematical programming - Linear Programming, Mixed Integer Programming etc , Stochastic Modelling - Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models. Familiarity to deploy and monitor ML models in production, delivering data products to end-users.

About Us Valiance is a global AI & Data analytics firm helping clients build cutting-edge technology solutions for digital transformation. We work with some of the marquee brands across India, US and APAC to build transformative solutions for Credit Risk, Fraud, Predictive Maintenance, Quality Inspection, Data lake, IOT analytics etc. Our team comprises 140+ professionals across Machine Learning, Data Engineering & Cloud expertise. Job Summary/Objective: The Data Scientist will be responsible for applying our pre-trained demand forecasting models to generate actionable insights and highly accurate forecasting outcomes. This role involves thorough data analysis, identifying trends and anomalies, interpreting results, and communicating findings effectively to a non-technical business audience. The ideal candidate is less focused on creating algorithms and more oriented towards solving business challenges and providing insights that make a tangible impact. Key Responsibilities: Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and anomalies in demand/Timeseries forecasting for Retail Industry very specific to Apparel and Footwear (must have) Model Utilization: Leverage existing pre-trained forecasting models, optimizing their performance by incorporating a nuanced understanding of data points and improving model outcomes based on data insights. Interpretation & Communication: Interpret model results and explain outcomes in simple, actionable terms for business stakeholders, ensuring clarity and relevance. Insights Generation: Develop insights that guide business decisions, aiming for highly accurate forecasting outcomes to meet business requirements. Collaboration: Work closely with cross-functional teams, including business stakeholders and analysts, to ensure forecasting outputs align with business objectives and provide real-world value. Continuous Improvement: Identify opportunities to improve model performance through better data usage and fine-tuning, rather than new model development. Required Skills & Qualifications: Experience: 3-8 years of experience in data science or a related field, specifically in Demand/Timeseries forecasting for Retail Industry very specific to Apparel and Footwear (must have) Technical Proficiency: Strong skills in data analysis, data visualization, and working with pre-trained ML models. Proficiency in Python, and SQL is preferred. Business Focus: Strong orientation towards solving business problems rather than a pure focus on machine learning algorithms. Communication Skills: Ability to clearly communicate insights and forecast results to non-technical stakeholders in simple, understandable language. Problem Solving: Demonstrated ability to interpret data, uncover actionable insights, and suggest practical solutions for business needs. Detail-Oriented: Thorough attention to detail, ensuring accuracy in forecasting and relevance of insights. Educational Background: Bachelors or Masters degree in Data Science, Statistics, Computer Science, or a related field.

About Team Myntra Data Science team delivers a large number of data science solutions for the company which are deployed at various customer touch points every quarter. The models create significant revenue and customer experience impact. The models involve real-time, near-real-time and offline solutions with varying latency requirements. The models are built using massive datasets. You will have the opportunity to be part of a rapidly growing organization and gain exposure to all the parts of a comprehensive ecommerce platform. You ll also get to learn the intricacies of building models that serve millions of requests per second at sub second latency. The team takes pride in deploying solutions that not only leverage state of the art machine learning models like graph neural networks, diffusion models, transformers, representation learning, optimization methods and bayesian modeling but also contribute to research literature with multiple peer-reviewed research papers. Roles and Responsibilities Responsible for developing data science and machine learning models for Myntra Storefront, Supply Chain and other areas Conversant with machine learning life cycles, model deployments etc. Theoretical understanding and practice of machine learning and expertise in one or more of the topics, such as Time Series, Forecasting and Optimization. Collaborating with Product and Business to formulate the problem into a Machine Learning model. Connecting with Platforms and Engineering teams to make sure the predictive models built are deployed and integrated into the systems. Working with the Data Platforms teams for understanding, and collecting the data. Qualifications & Experience Knowledge on data structures, algorithms and efficient processing of large datasets Well-versed with Python. Good to have publications. 2-4 years of experience with MTech, MS by Research or PhD in Computer Science/Electrical Engineering, or post graduate degree in Statistics, Operations Research, or Mathematics Experience in developing efficient Time Series and forecasting solutions. Good to have some experience with large-scale nonlinear & integer programming algorithms - hands on with optimization solvers (CPLEX, Gurobi, COIN-OR etc.) Good to have skills in general Machine Learning and Deep Learning such as Natural Language Processing (NLP): Skills in NLP to develop models that understand and generate human language. Computer Vision: Knowledge of computer vision techniques to interpret images and videos, including object identification and classification. DevOps: Familiarity with DevOps principles and practices for deploying and managing machine learning models in production environments LLM and GenAI Models: Understanding of Large Language Models (LLM) and Generative AI (GenAI) models, including prompt engineering, model evaluation, optimization, and deployment. Domain Knowledge: Expertise in a specific industry or field, enabling better understanding of data and business needs. Ethical Data Science: Awareness of ethical considerations in data science, including privacy, bias and fairness. Collaboration: Strong communication and teamwork skills for effective collaboration with cross-functional teams, including engineers, product managers, and designers.

We are looking for a Senior Data Scientist who is passionate about solving complex business problems using data. The ideal candidate will have strong hands-on experience in Python , SQL , and advanced machine learning algorithms , along with domain expertise in forecasting , pricing optimization , or inventory planning . You will work closely with cross-functional teams including product, engineering, and business stakeholders to drive data-driven strategies. Key Responsibilities: Design, build, and deploy predictive and optimization models for use cases such as demand forecasting , dynamic pricing , or inventory optimization . Translate business problems into analytical frameworks and provide actionable insights. Build and maintain scalable data pipelines and model workflows using Python and SQL. Collaborate with data engineers to ensure model integration into production systems. Present findings and recommendations to leadership using data visualizations and storytelling. Stay current with the latest techniques in machine learning , statistics , and operations research . Lead and mentor junior data scientists and analysts when required. Required Skills and Experience: 5+ years of experience in a Data Science or Analytics role with a strong business impact. Strong programming skills in Python (pandas, scikit-learn, statsmodels, etc.). Proficiency in SQL for data extraction, transformation, and manipulation. Deep understanding of machine learning algorithms (regression, classification, clustering, time series forecasting). Experience with one or more of the following domains: Demand Forecasting Price Optimization Inventory Optimization / Supply Chain Analytics Strong problem-solving and quantitative skills. Experience working with large datasets and distributed computing tools (e.g., Spark, Hadoop) is a plus. Familiarity with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn). Preferred Qualifications: Masters or PhD in Computer Science, Statistics, Mathematics, Economics, Operations Research, or a related field. Experience in retail, e-commerce, manufacturing, or logistics is a strong plus. Exposure to optimization libraries (e.g., PuLP, OR-Tools, Gurobi) is a bonus. Experience deploying models using MLOps tools or platforms is a plus.

Entity :- Accenture Strategy & Consulting Team :- Global Network Data & AI Practice :- Life Sciences Title :- Ind & Func AI Decision Science Consultant Job Location :- Delhi, Gurgaon, Mumbai, Bangalore About Strategy & Consulting Global Network :- Accenture S&C Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition. WHATS IN IT FOR YOU An opportunity to work on high-visibility projects with top Pharma clients around the globe. Potential to Co-create with leaders in strategy, industry experts, enterprise function practitioners, and business intelligence professionals to shape and recommend innovative solutions that leverage emerging technologies. Ability to embed responsible business into everythingfrom how you service your clients to how you operate as a responsible professional. Personalized training modules to develop your strategy & consulting acumen to grow your skills, industry knowledge, and capabilities. Opportunity to thrive in a culture that is committed to accelerating equality for all. Engage in boundaryless collaboration across the entire organization. What you would do in this role Support delivery of small to medium-sized teams to deliver consulting projects for global clients. Responsibilities may include strategy, implementation, process design, and change management for specific modules. Work with the team or as an Individual contributor on the project assigned which includes a variety of skills to be utilized from Data Engineering to Data Science Develop assets and methodologies, point-of-view, research, or white papers for use by the team and the larger community. Work on variety of projects in Data Modeling, Data Engineering, Data Visualization, Data Science etc., Acquire new skills that have utility across industry groups. Support strategies and operating models focused on some business units and assess likely competitive responses. Also, assess implementation readiness and points of greatest impact. Make presentations wherever required to a known audience or client on functional aspects of his or her domain. Qualification Who are we looking for Bachelors or Masters degree in Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems, or other Quantitative field. Proven experience (2+ years) in working on Life Sciences/Pharma/Healthcare projects and delivering successful outcomes. Understanding of Pharma data sets commercial, clinical, RWE (Real World Evidence) & EMR (Electronic medical records) Leverage ones hands on experience of working across one or more of these areas such as real-world evidence data, R&D clinical data, digital marketing data. Hands-on experience in building and deployment of Statistical Models/Machine Learning including Segmentation & predictive modeling, hypothesis testing, multivariate statistical analysis, time series techniques, and optimization. Hands-on experience with handling Datasets like Komodo, RAVE, IQVIA, Truven, Optum etc. Proficiency in Programming languages such as R, Python, SQL, Spark, etc. Ability to work with large data sets and present findings/insights to key stakeholders; Data management using databases like SQL. Experience with any of the cloud platforms like AWS, Azure, or Google Cloud for deploying and scaling language models. Experience with any of the Data Visualization tools like Tableau, Power BI, Qlikview, Spotfire is good to have. Excellent analytical and problem-solving skills, with a data-driven mindset. Proficient in Excel, MS Word, PowerPoint, etc. Ability to solve complex business problems and deliver client delight. Strong writing skills to build points of view on current industry trends. Good communication, interpersonal, and presentation skills Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.