5 Data Scientists Jobs

ETL Process Design: Designing and developing ETL processes using Talend for data integration and transformation. Data Extraction: Extracting data from various sources, including databases, APIs, and flat files. Data Transformation: Transforming data to meet business requirements and ensuring data quality. Data Loading: Loading transformed data into target systems, such as data warehouses or data lakes. Job Scheduling: Scheduling and automating ETL jobs using Talend's scheduling tools. Performance Optimization: Optimizing ETL workflows for efficiency and performance. Error Handling: Implementing robust error handling and logging mechanisms in ETL processes. Data Profiling: Performing data profiling to identify data quality issues and inconsistencies. Documentation: Documenting ETL processes, data flow diagrams, and technical specifications. Collaboration with Data Teams: Working closely with data analysts, data scientists, and other stakeholders to understand data requirements. Min 4 to Max 7yrs of Relevant exp. Locations : Mumbai, Delhi NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, Remote

We are seeking a highly experienced and technically adept Lead AI/ML Engineer to spearhead the development and deployment of cutting-edge AI solutions, with a focus on Generative AI and Natural Language Processing (NLP). The ideal candidate will be responsible for leading a high-performing team, architecting scalable ML systems, and driving innovation across AI/ML projects using modern toolchains and cloud-native technologies. Key Responsibilities Team Leadership: Lead, mentor, and manage a team of data scientists and ML engineers; drive technical excellence and foster a culture of innovation. AI/ML Solution Development: Design and deploy end-to-end machine learning and AI solutions, including Generative AI and NLP applications. Conversational AI: Build LLM-based chatbots and document intelligence tools using frameworks like LangChain , Azure OpenAI , and Hugging Face . MLOps Execution: Implement and manage the full ML lifecycle using tools such as MLFlow , DVC , and Kubeflow to ensure reproducibility, scalability, and efficient CI/CD of ML models. Cross-functional Collaboration: Partner with business and engineering stakeholders to translate requirements into impactful AI solutions. Visualization & Insights: Develop interactive dashboards and data visualizations using Streamlit , Tableau , or Power BI for presenting model results and insights. Project Management: Own delivery of projects with clear milestones, timelines, and communication of progress and risks to stakeholders. Required Skills & Qualifications Languages & Frameworks: Proficient in Python and frameworks like TensorFlow , PyTorch , Keras , FastAPI , Django NLP & Generative AI: Hands-on experience with BERT , LLaMA , Spacy , LangChain , Hugging Face , and other LLM-based technologies MLOps Tools: Experience with MLFlow , Kubeflow , DVC , ClearML for managing ML pipelines and experiment tracking Visualization: Strong in building visualizations and apps using Power BI , Tableau , Streamlit Cloud & DevOps: Expertise with Azure ML , Azure OpenAI , Docker , Jenkins , GitHub Actions Databases & Data Engineering: Proficient with SQL/NoSQL databases and handling large-scale datasets efficiently Preferred Qualifications Masters or PhD in Computer Science, AI/ML, Data Science, or related field Experience working in agile product development environments Strong communication and presentation skills with technical and non-technical stakeholders

Design, develop, and maintain data pipelines and ETL processes using AWS and Snowflake. Implement data transformation workflows using DBT (Data Build Tool). Write efficient, reusable, and reliable code in Python. Optimize and tune data solutions for performance and scalability. Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions. Ensure data quality and integrity through rigorous testing and validation. Stay updated with the latest industry trends and technologies in data engineering. Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience as a Data Engineer or similar role. Strong proficiency in AWS and Snowflake. Expertise in DBT and Python programming. Experience with data modeling, ETL processes, and data warehousing. Familiarity with cloud platforms and services. Excellent problem-solving skills and attention to detail. Strong communication and teamwork abilities.

Skill required: Sales Insights & Intelligence - Sales Enablement Designation: Analytics and Modeling Manager Qualifications: Any Graduation Years of Experience: 9+ years About Accenture What would you do As the Team Lead, and a key member of the Sales Operations Transformation - Data Analytics, Reporting & Visualization team, you will head a cross-functional team of Data Scientists and Visualization experts working within the Sales Operations transformation space. The ideal candidate brings a strong background in advanced analytics, business intelligence, and sales domain knowledge, along with a proven track record in project delivery, stakeholder management, and team leadership.Key responsibilities include:Drive and oversee the design, development, and deployment of data science models and visualization solutions that support sales strategy, performance tracking, and revenue optimization.Drive collaboration across functional, technical, and global teams to ensure solutions are aligned with business needs and deliver measurable outcomes.Manage project timelines, resource planning, and risk mitigation across multiple workstreams while maintaining high standards of quality and delivery.Serve as a subject matter expert in Sales Operations analytics, providing thought leadership, mentorship, and guidance to both technical and non-technical stakeholders..This is a high-impact role where technical acumen meets business strategy, and your work will directly influence sales operations transformation through AI-powered innovation. What are we looking for We are looking for individuals who bring a blend of strategic thinking, operational expertise, and a passion for transformation. The ideal candidate will have the following skillset:Strong background in Sales Operations, CRM data, and sales process optimization.Proven experience in data analytics, data science, and business intelligence.Proven experience in leading teams that deliver both advanced statistical models and interactive dashboards.Deep understanding of Python (Pandas, NumPy, Scikit-learn) for data modeling and analytics.Strong command over Power Query, Power Pivot, Power BI and BI architecture for visual storytelling and dashboarding.Hands-on experience with SQL, data management, and data modeling practices.Excellent stakeholder management and communication skills.Experience working with global, cross-functional teams.Proficiency in Microsoft Excel for data analysis and reporting.Experience in driving transformation initiatives through automation and advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Roles and Responsibilities: Strategic Leadership & DeliveryoLead the end-to-end delivery of AI, analytics, and visualization solutions across sales operations workstreams.oAlign team objectives with Sales Excellence and Sales Transformation strategyoDrive solution design, data strategy, and execution across data science and BI tracks.oOversee solution scalability, reusability, and integration into business processes.Team ManagementoManage, mentor, and grow a high-performing team including L8/L9 Data Scientists and Power BI developers.oProvide technical and functional guidance to team members.oConduct regular performance reviews, skill development sessions, and team health checks.oOversee capacity planning and work allocation.Stakeholder EngagementoCollaborate with senior business leaders, sales stakeholders, and global teams to define problem statements, KPIs, and success metrics.oServe as the client-facing SME for all analytics and visualization needs in the sales domain.oEnsure strong communication of findings, models, and visualizations through effective storytelling.Technical OversightoEnsure high-quality delivery of data science models (predictive, diagnostic, prescriptive) and dashboards.oReview and validate model outcomes, dashboards, and visual designs.oEncourage adoption of best practices in code management, versioning, and model documentation.oEnsure data quality, governance, and secure access across platforms Qualification Any Graduation

As the Lead Data Scientist at Siemens Advanta, you will play a pivotal role in driving data-driven decision-making and leading the development and implementation of advanced analytical models. You will work closely with cross-functional teams to identify business challenges, design data-driven solutions, and provide actionable insights to optimize processes and drive innovation. We are looking for: Lead AI Engineer Youll make a difference by: Lead and manage a team of data scientists, providing guidance, mentorship, and technical expertise. Collaborate with stakeholders to understand business objectives and develop data science strategies aligned with those objectives. Design, develop, and implement advanced machine learning and statistical models to solve complex business problems. Conduct exploratory data analysis, data cleansing, and feature engineering to prepare datasets for analysis. Explore and utilize various data mining and machine learning techniques to extract valuable insights and patterns from large datasets. Develop predictive/prescriptive models, algorithms, and prototypes to support business. Should have working knowledge of handling IOT and IIOT data and handling traditional use cases like anomaly detection for a multi-sensor system. Should have hands-on experience in Forecasting using traditional ML and Deep Networks Perform statistical analysis, hypothesis testing, and A/B testing to evaluate the effectiveness of models and algorithms. Communicate findings and insights to technical and non-technical stakeholders through reports, presentations, and data visualizations. Should understand CI/CD processes in product deployment and used it in delivery. Should have an understanding of the Dockerization, REST APIs Working knowledge on software development processes. Stay up to date with the latest trends and advancements in data science, machine learning, and AI technologies and identify opportunities to apply them to improve business outcomes. Youll win us over by 8+ years of experience in data science and/or data analysis with a proven track record of developing ML models and algorithms. A masters or Ph.D. degree in Data Science, Computer Science, Statistics, or a related field Strong programming skills in languages such as Python, R, or C++. Exposure to the industrial engineering domain is preferred. Knowledge of big data technologies such as Hadoop, Spark, or Hive is a plus. Proficient in the use of data science tools Excellent analytical/statistical skills. Proactive and willing to learn new technologies. Excellent verbal, written and presentation skills.