19428 Statistics Jobs - Page 21

Role Description As a Technical Lead - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be open to new ideas and be willing to learn and develop new skills. Should also be able to work well under pressure and manage multiple tasks and priorities. Nice-to-have skills Qualifications 7-9 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Nice-to-have skills Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Nice-to-have skills Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Technical Lead - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be open to new ideas and be willing to learn and develop new skills. Should also be able to work well under pressure and manage multiple tasks and priorities. Qualifications 7-9 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Technical Lead - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be open to new ideas and be willing to learn and develop new skills. Should also be able to work well under pressure and manage multiple tasks and priorities. Qualifications 7-9 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills : Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : Advanced AI and GenAI for Problem Discovery, RCA and Action Recommendation : Lead the data scientists in hands-on mode developing and deploying advanced machine learning models, including anomaly detection, predictive analytics, causal inferencing and action recommendation models, to autonomously discover problems and identify root causes and recommend actions in real-time and batch processing scenarios Gen-AI-Powered Analysis and Insights Generation: Lead the data scientists in hands-on mode creating and fine-tuning Generative AI models to assist in analysis creation for problem discovery, translating complex data patterns and root cause findings into actionable, natural language insights for business stakeholders. Implement prompt engineering and fine-tuning techniques to enhance the relevance and accuracy of insights. Reference Architectures : Work with Technical Architects to evolve frameworks for augmenting and evolving batch processing data architectures with streaming architectures to support connected data and ML pipeline executions in real-time. Client Deployments of the Platform: Consult and provide guidance for creating automated data pipelines for raw data and engineered features ensuring data quality, integrity, and accessibility for model training and inference. Development of Use Cases: Lead and support development of the use cases on the platform for various vertical specific problem statements. Leadership and Collaboration: Lead and mentor a team of data scientists and machine learning engineers, Pre-sales: Support pre-sales, marketing hyper-scaler partnerships and other sales activities such as RFPs by providing subject matter expertise during scoping and designing of the engagements. Technical Skills : In-depth conceptual understanding of Statistics, Classical Machine Learning, Deep Learning and GenAI Able to understand the nuances of business problems in various domains, quickly grasp the problem discovery analysis and modelling imperatives and translate those into the requirements for AI models Significant exposure to various proprietary & open-source cloud-based Machine Learning platforms such as Amazon Sagemaker / Azure Machine Learning Studio / Google Datalab ML Engine AutoML / H2O etc. Experience in leveraging open-source LLMs and prompt engineering and RAG based SLM model development Hands-on with excellent ML programming skills in Python using open-source libraries Qualifications Experience in working with RDBMS and NoSQL databases; Exposure to Big Data technologies 14-16 years of Machine Learning model development and application experience Experience in building cloud-based products that implement ML modelling as a service would be ideal

Role Description : As a Technical Lead - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be open to new ideas and be willing to learn and develop new skills. Should also be able to work well under pressure and manage multiple tasks and priorities. Qualifications 7-9 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Software Engineer - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Qualifications 3-5 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description : As a Technical Lead - Data Analysis at Incedo, you will be responsible for analyzing and interpreting large and complex datasets to extract insights and identify patterns. You will work with data analysts and data scientists to understand business requirements and provide data-driven solutions. You will be skilled in data analysis tools such as Excel or Tableau and have experience in programming languages such as Python or R. You will be responsible for ensuring that data analysis is accurate, efficient, and scalable. Roles & Responsibilities: Analyzing and interpreting complex data sets using statistical and data analysis tools Developing and implementing data-driven insights and solutions Creating and presenting reports and dashboards to stakeholders Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data analysts. Technical Skills Skills Requirements: Proficiency in data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Knowledge of statistical analysis techniques such as hypothesis testing, regression analysis, or time-series analysis. Familiarity with data visualization and reporting tools such as Tableau, Power BI, or Looker. Understanding of data exploration and discovery techniques such as clustering, anomaly detection, or text analytics. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be open to new ideas and be willing to learn and develop new skills. Should also be able to work well under pressure and manage multiple tasks and priorities. Qualifications 7-9 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Role Description As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers. Responsibilities Utilize your expertise in online scraping techniques to gather and process data from various sources. Apply advanced machine learning and AI algorithms to clean, structure, and analyse complex datasets. Collaborate with our team to develop and deploy scalable data solutions. Contribute to the optimization of our data infrastructure and analytics pipelines. Generate actionable insights for business improvements Qualifications Bachelor's or Master's degree in quantitative field (Data Science, Statistics, Mathematics, Computer Science, etc.). At least 5 years of experience in data science roles, preferably within the financial and/or life sciences industry. Deep understanding of predictive modelling, machine-learning, clustering and classification techniques, and algorithms. Fluency in programming languages commonly used in data science (at least Python). Fluency in using AI code editors like Windsurf / Cursor. Familiarity with Java is a plus. Strong understanding of machine learning techniques, with experience implementing models of varying complexity. Ability to work independently and manage multiple projects simultaneously. Excellent communication skills and a collaborative mindset.

PROFESSIONAL SUMMARY Compensation Specialist with 4+ years of progressive experience in compensation analysis. Proficiency in leveraging compensation systems and survey data to support organizational compensation strategy while ensuring regulatory compliance. QUALIFICATIONS Minimum 4-5 years of progressive experience in compensation analysis Advanced Excel skills and proficiency with HRIS and compensation management systems Strong analytical and statistical skills with ability to interpret complex data Knowledge of compensation best practices and regulatory requirements Experience with compensation survey participation and interpretation Bachelors degree in human resources, Business, Finance, or related field CORE COMPETENCIES Data analysis Critical thinking and problem-solving Project management Effective communication Attention to detail PROFESSIONAL EXPERIENCE Conducted market pricing analysis using compensation survey data to establish competitive pay ranges Performed job evaluations and classifications to determine appropriate pay grades Maintained compensation structures, including salary bands and job families Supported annual compensation planning processes Responded to complex compensation inquiries and provided guidance to HR business partners Assisted with the implementation of compensation policies Monitored compliance with relevant compensation laws and regulations

About Company Founded in 2011, ReNew, is one of the largest renewable energy companies globally, with a leadership position in India. Listed on Nasdaq under the ticker RNW, ReNew develops, builds, owns, and operates utility-scale wind energy projects, utility-scale solar energy projects, utility-scale firm power projects, and distributed solar energy projects. In addition to being a major independent power producer in India, ReNew is evolving to become an end-to-end decarbonization partner providing solutions in a just and inclusive manner in the areas of clean energy, green hydrogen, value-added energy offerings through digitalisation, storage, and carbon markets that increasingly are integral to addressing climate change. With a total capacity of more than 13.4 GW (including projects in pipeline), ReNew’s solar and wind energy projects are spread across 150+ sites, with a presence spanning 18 states in India, contributing to 1.9 % of India’s power capacity. Consequently, this has helped to avoid 0.5% of India’s total carbon emissions and 1.1% India’s total power sector emissions. In the over 10 years of its operation, ReNew has generated almost 1.3 lakh jobs, directly and indirectly. ReNew has achieved market leadership in the Indian renewable energy industry against the backdrop of the Government of India’s policies to promote growth of this sector. ReNew’s current group of stockholders contains several marquee investors including CPP Investments, Abu Dhabi Investment Authority, Goldman Sachs, GEF SACEF and JERA. Its mission is to play a pivotal role in meeting India’s growing energy needs in an efficient, sustainable, and socially responsible manner. ReNew stands committed to providing clean, safe, affordable, and sustainable energy for all and has been at the forefront of leading climate action in India. Job Description As a Senior Data Scientist, you will be responsible for providing simple and intuitive solutions to the most complex problems in renewable industry. This will involve building machine learning and deep learning models which are coupled with contextual business knowledge. You will also use both management experience and data science expertise to lead analytics projects and mentor junior data scientists . You will be an integral part of conceptualizing, scoping and delivering complex analytics projects . You will do and oversee the development, testing and maintenance of analytical models which mimic business decisions. You will work with a world-class team of site managers, subject experts, data engineers and data scientists to build the next generation data-driven renewable company. Additionally, you will be responsible for continuously identifying opportunities to improve the ways of working and structuring within the analytics center of excellence. Roles and Responsibilities Implement data science solutions which may involve machine learning or data science techniques to increase and optimize outputs Assess the effectiveness and accuracy of data sources and data gathering techniques Manage analytics strategy across multiple use cases Provide analytical expertise in the process of model development, refining and implementation in a variety of analytics problems spread across a variety of domains Oversee and mentor large team of associate and junior-level data scientists, de-bottlenecking issues related to project execution Work closely with translators and business teams to develop and implement analytics solutions Collaborate with the engineering team to integrate data science solutions into production environments and deploy scalable solutions Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner Acquire extensive knowledge of renewables industry practices and implement tailor made techniques to solve problems relevant to the same Promote a culture of continuous learning, sharing knowledge, and staying up-to-date with emerging technologies and best practices in data science Profile & Eligible Criteria Bachelor's in Computer Science, Data Science, Statistics, Mathematics, or a related field. Master's degree preferred Proven experience of 4-6 years as a Data Scientist or in a similar role, with a strong track record of delivering successful data science projects Sound theoretical and practical knowledge of working in statistical analysis, machine learning techniques, and deep learning frameworks with solid of understanding of techniques related to regression, classification, NLP, Computer Vision, Generative AI Proficiency in Python is a must. Proficiency in SQL for data manipulation is a plus Worked in developing analytics solutions in 3-4 domains Excellent communication skills to effectively manage a team and collaborate with stakeholders in cross-functional teams Communication skills: Basic level of articulation of theoretical concepts Ability to communicate with cross functional roles is a plus Teamwork: Displays ability to work both as an individual and as a self-motivated team player Has worked in large teams with an agile setup in the past

We are looking for either (1) 1-3 years of market research experienced professionals or (2) young talents who are Economics or Statistics Master Degree pass-outs of 2023 or '24 or '25 from highly acclaimed educational institutions like Indira Gandhi Institute of Developmental Research or Ashoka University (including the ASP program) or Madras School of Economics or Delhi School of Economics or Narsee Monjee Institute of Management Studies . 1) We love ' great story listeners and tellers ' who can mesh their personal experiences with what they hear from people and the market. We love to see these reflected in Canva decks & video edits . 2) We love ' great statistics and SPSS ' type of skills and good acquaintance with how to maximise the best out of ' Sawtooth kind of questionnaire scripting ' tools. We love excel mastery as well. To ensure long term best fit , we request for a 3-6 months paid internship before final job confirmation . Role: 1) Lead and execute qualitative or / and quantitative market research ventures for businesses. 2) Provide business solutions enabled with the research evidence and the team's marketing experience. 3) Utilise the strengths of the team to bring the best out of them. 4) We would love to work with your individual style to bring diversity in our deliveries. 5) The KPIs of your success would be all brands and business focussed . You would be co-working with ex-Unilever, HUL, GSK - Marketing and CMI professionals to develop your edge Responsibilities 1) Hunt for consumer white spaces for new business development of Indian and international brands . 2) Craft consumer research proposals enabled with past evidence to value-add beyond what brands & businesses want. 3) Write qual discussion guides / quant questionnaires with an element of uniqueness, to bring out the unvoiced elements of people 4) Analyse ( qual ) using narrative style from stories, inductive style while connecting the dots, suggestive style while providing the so-whats and recommendations to brands & businesses 5) Analyse ( quant ) with a pattern seeking approach from data cross-tabulations and use a combination of multivariate techniques like factor, cluster, discriminant or random forest kind of machine learning algorithms 6) Craft reports while providing summaries, 'so-whats' and recommendations for growth of brands & businesses Qualifications 1) Economics or Statistics Master Degree pass-outs of 2023 or '24 or '25 from highly acclaimed educational institutions like I ndira Gandhi Institute of Developmental Research or Ashoka University (including the ASP program) or Madras School of Economics or Delhi School of Economics or Narsee Monjee Institute of Management Studies . 2) Should have great academic results in the masters program something like 85%+ . 3) To ensure long term best fit , we request for a 3-6 months paid internship before final job confirmation .

Minimum qualifications: Bachelor's degree or equivalent practical experience. 5 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data. 5 years of experience managing projects and defining project scope, goals, and deliverables. Preferred qualifications: Master’s or Ph.D. degree in a quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Operations Research etc.) 5 years of experience in a large-scale data analysis or data science setting, including abuse and fraud disciplines, with a focus on web security, harmful content moderation and threat analysis. Experience scripting languages in (e.g., C/C++) with proficiency in programming languages (e.g., Python, Julia) and database languages like SQL. Experience with prompt engineering and fine-tuning LLMs. Proficiency in applying machine learning techniques to large datasets. About The Job Trust & Safety team members are tasked with identifying and taking on the biggest problems that challenge the safety and integrity of our products. They use technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse across Google products like Search, Maps, Gmail, and Google Ads. On this team, you're a big-picture thinker and strategic team-player with a passion for doing what’s right. You work globally and cross-functionally with Google engineers and product managers to identify and fight abuse and fraud cases at Google speed - with urgency. And you take pride in knowing that every day you are working hard to promote trust in Google and ensuring the highest levels of user safety. The AI Safety Protections team within Trust and Safety develops and implements cutting-edge AI/LLM-powered solutions to ensure the safety of generative AI across Google's products. This includes safeguards for consumer products, enterprise offerings (Vertex AI), on-device applications, as well as foundational models (Gemini, Juno, Veo) in collaboration with Google DeepMind. We are a team of passionate data scientists and machine learning experts dedicated to mitigating risks associated with generative AI, and addressing real-world safety with LLM/AI technology (e.g., imminent threat, child safety). As a member of our team, you will have the opportunity to apply the latest advancements in AI/LLM, work with teams developing cutting-edge AI technologies, as well as protecting the world from real-world harms. This role works with sensitive content or situations and may be exposed to graphic, controversial, or upsetting topics or content. Responsibilities Develop scalable safety solutions for AI products across Google by leveraging advanced machine learning and AI techniques. Apply statistical and data science methods to examine Google's protection measures, uncover potential shortcomings, and develop actionable insights for continuous security enhancement. Drive business outcomes by crafting compelling data stories for a variety of stakeholders, including executive leadership. Develop automated data pipelines and self-service dashboards to provide timely insights at scale. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .

Bangalore, India Who are we? Aarki is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC. The role? We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with senior data scientists and other team members to drive impactful machine learning projects and contribute to innovative solutions. This is an on-site role, 5 days a week, based in our Bengaluru, India office. Join us in pushing the boundaries of AI and mobile advertising in a collaborative environment that fosters creativity and growth. We offer a competitive salary, comprehensive benefits, and significant opportunities for career advancement. What will you do? Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud. Collaborate with senior data scientists and cross-functional teams (product, engineering, and business) to integrate models into production workflows. Analyze the impact of integrating new data sources and features into our models. Build and maintain data pipelines to process and prepare large datasets for model training and evaluation. Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities. Learn and stay informed about emerging techniques in machine learning and data science, applying them as appropriate to enhance our products. What are we looking for? Bachelor’s degree in Mathematics, Physics, Computer Science, or a related technical field. At least 1 year of professional experience in machine learning, statistical analysis, and data analysis. Proficiency in Python and SQL. Experience with machine learning techniques such as regression, classification, and clustering. Familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn). Strong grasp of probability, statistics, and data analysis principles. Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders. Familiarity with AdTech, personalization and pricing algorithms, or system programming languages including C++ and Rust is a plus.

Introduction A career in IBM Software means you’ll be part of a team that transforms our customer’s challenges into solutions. Seeking new possibilities and always staying curious, we are a team dedicated to creating the world’s leading AI-powered, cloud-native software solutions for our customers. Our renowned legacy creates endless global opportunities for our IBMers, so the door is always open for those who want to grow their career. IBM’s product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive Your Role And Responsibilities The Data Scientist role requires a highly analytical individual proficient in Python programming, database management, and data science methodologies. You’ll focus on extracting insights from data, developing and implementing machine learning models, managing big data infrastructure, and supporting AI-driven product development. Key Responsibilities Data Collection and Cleansing: Collect and cleanse data from diverse sources to ensure high-quality datasets for decision-making. Data Exploration and Visualization: Explore and visualize data using advanced techniques to uncover insights and trends. Statistical Analysis: Apply statistical and mathematical techniques to provide robust analytical foundations for predictive modeling. Machine Learning and Deep Learning: Develop and implement machine learning and deep learning models to address business challenges. ML-Ops / AI-Ops: Demonstrate expertise in ML-Ops / AI-Ops practices to ensure efficient model deployment and management. Big Data Management: Manage big data infrastructure and execute data engineering tasks for efficient data processing. Version Control and Collaboration: Utilize version control systems like Git for maintaining codebase integrity and fostering collaboration. AI-Driven Product Development: Design, create, and support AI-driven products to deliver impactful solutions aligned with user needs and business objectives. Preferred Education Master's Degree Required Technical And Professional Expertise Industry Experience: Minimum of 5 years of experience in the IT industry, with a focus on data science and AI, specifically in implementing data-driven solutions Technical Proficiency: Proficient in Python programming, NLP techniques, and AI Frameworks (e.g., Hugging Face). Knowledge of common machine learning algorithms and frameworks: linear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Database Management: Knowledge of SQL and NoSQL database management. Data Science Skills: Strong background in data science, statistics, mathematics, and analytical techniques. Machine Learning Expertise: Expertise in machine learning and deep learning methodologies, including foundation models. Preferred Technical And Professional Experience Deep Learning Experience: Hands-on experience in data science for 5+ years with a minimum of 4 years in deep learning. Big Data Technologies: Familiarity with big data technologies and data engineering practices. Familiarity with MLOps practices and tools (e.g., MLflow, Airflow). Cloud Computing Experience: Experience with cloud computing platforms (AWS/Azure/Google/IBM) for leveraging advanced cloud-based services.

Core Skills • Bachelor’s degree in computer science or a related field OR master’s degree in statistics, economics, business economics, econometrics, or operations research. • 5-10 years of experience in the Analytics/Data Science domain. • Experience with Generative AI techniques and tools. • Familiarity with ETL methods, data imputation, data cleaning, and outlier handling. • Familiarity with AWS cloud platform and AI/ML services. • Knowledge of databases and associated tools such as SQL. Technical Skills – Desirable: • Expertise in Deep learning, Segmentation, Classification and Ensemble techniques • Multi-agent frameworks, and Evaluation frameworks. • Proficiency in programming languages such as Python.

We are seeking a talented individual to join our Data Analytics & Insight team at Marsh Mc Lennan. This role will be based in Mumbai. This is a hybrid role that has a requirement of working at least three days a week in the office We will count on you to: Become proficient in the MPower system to train colleagues, ensure accurate reconciliation with month-end finance reports, and collaborate with opportunity owners and client teams to resolve data anomalies. Create and maintain dynamic data views and dashboards that present key sales insights and performance metrics to support various initiatives, including sales forums and leadership meetings. Establish and define KPI dashboards to translate sales data into actionable insights, prioritize opportunities, and evaluate overall performance. Own the reporting process for daily, weekly, and monthly business metrics, delivering comprehensive insights to the senior management team to aid in business assessment and decision-making. Effectively manage multiple projects simultaneously, adhering to tight timelines while maintaining high-quality outputs. . What you need to have: Bachelors degree in Business, Data Analytics, or a related field; a Masters degree in Statistics, Business Analytics, or a similar discipline is a plus. 7-8 years of proven experience in sales reporting and analytics, with a strong ability to interpret data and generate actionable insights that drive business strategies and enhance sales performance. Proficiency in data visualization tools and reporting software, enabling the creation of dynamic dashboards and comprehensive reports that effectively communicate sales metrics and trends to stakeholders. Strong project management skills with the ability to prioritize tasks and manage resources effectively, demonstrating agility by adapting to evolving business needs and requirements. Excellent communication skills, with the ability to articulate ideas clearly and effectively across various channels and audiences, ensuring alignment and understanding within the team and with stakeholders. Proven ability to build and maintain strong interpersonal relationships across the business and with stakeholders, fostering collaboration and trust to achieve common goals. Strong analytical thinking skills combined with a strategic mindset to understand and structure business problems, effectively presenting insights through compelling visual storytelling that engages stakeholders while aligning technical solutions with business objectives. Solid problem-solving abilities to identify and resolve data discrepancies, ensuring data integrity and accuracy while leveraging insights to drive strategic decision-making and enhance overall business performance Eligibility Minimum 12 months experience as Manager (Grade D2) / Senior Manager (Grade E) Should have at least On-Track or equivalent rating in last appraisal. Should not be under any Performance Counselling Plan or had any official disciplinary action within the last 3 months. Should not have applied for any other IJP in the last 3 months

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Lead, Data Scientist Our Purpose We work to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results. Job Title: Data Scientist (Credit Risk), Advanced Analytics Job Description Summary Overview Advanced Analytics drives AI-based solutions and products at a globally scalable level across the different customer lifecycle stages, credit risk management and strategic analytics. Our Credit Risk management area serves as a key differentiator to optimize and grow revenue from consumers and small businesses for Mastercard. To this end, developing and manging a suite of product solutions through internal and external partnerships, creative constructs, application of AI-based solutions, solid frameworks and executable roadmaps are crucial drivers for commercialization and business impact. This role is for a Lead Data Scientist that will work across Product, Client Services & Delivery, Data & Engineering and the broader teams, to deliver truly differentiated Credit products, leveraging rich data resources, AI platform capabilities and near real-time execution. The Global Credit Risk Product team is executing on an exciting consumer capability initiative and this role is central in that vision, from concept, technical design to market release and optimization. This role is positioned to drive new ideas forward by combining creative thought leadership with innovation and industry best practices. By entering in the early phase of a truly transformative and impactful strategic initiative, the experience is certain to be rewarding. This role will report into the Vice President of Data Science & AI within Advanced Analytics. The Successful Candidate’s Primary Responsibilities Will Be To: Drive the evolution of Advanced Analytics products with an impact focused on data science and engineering Participate in the exploration, application and development of data science for product development Participate in identification and evaluation of AI/ML techniques and tools to deliver models and analytics for product development Continuously innovate and determine new data science approaches & technologies to solve business problems and generate business insights & recommendations Partner with roles across the organization including product, engineering, and sales to determine the highest priority data science problems to solve in a customer-centric framework Evaluate trade-offs between many possible analytics solutions to a problem, taking into account performance, usability, technical feasibility, timelines, and differing stakeholder opinions to make a decision Break large solutions into smaller, releasable milestones to collect data and feedback from product managers, clients and other stakeholders Evangelize releases to users, incorporating feedback, and tracking usage to inform future development Work with small, cross-functional teams to define vision, establish team culture and processes Consistently focus on key drivers of organization value and prioritize operational activities accordingly Identify and act upon product improvement opportunities Provide technical leadership of junior colleagues as a senior member of the data science team, through technical and non-technical mentoring This role requires the successful candidate to have the following: Prior experience in working in a data science product development role Strong hands-on experience in Advanced Analytics, Machine Learning, Deep Learning, Advanced Statistics etc. High proficiency in Python, Spark, SQL, R and be able to navigate across multiple languages Preferably with hands-on experience with Hadoop big data tools (Hive, Impala, Spark) or Databricks Demonstrated quantitative and problem-solving abilities including application to real business problems Strong project management skills and ability to meet business deadlines and execution Motivated, flexible, self-directed, and desire to lead small project teams as applicable Curiosity, creativity, and excitement for technology and innovation and outside-in perspectives Ability to multi-task and strong attention to detail including data utilized, methodology, results and validation Outstanding communication and organizational skills Masters preferred in Quantitative discipline like Physical Sciences, Mathematics, Statistics, Economics, Engineering etc. 7-10 years of experience in Data Science function supporting Products COVID-19 Considerations We value the safety of each member of our community because we know we’re all in this together. In many locations, which may change over time, we’ve implemented a virtual hiring process and continue to interview candidates by video or phone. In addition, in some locations, only individuals who have been fully vaccinated will be permitted inside Mastercard offices until further notice. In the US, Mastercard is a government contractor, which may legally require most Mastercard employees to be vaccinated unless a verified approved medical or religious exemption is granted. Further, we are currently making every effort towards having employees return to work in the office 2 days per week, if that makes sense for their team. Everyone must be vaccinated to enter Mastercard offices at this time. Therefore, we expect all candidates to be vaccinated or to be approved for a medical or religious accommodation prior to commencing work at Mastercard. In the US, Mastercard is an inclusive Equal Employment Opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. If you require accommodations or assistance to complete the online application process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly. Corporate Security Responsibility All Activities Involving Access To Mastercard Assets, Information, And Networks Comes With An Inherent Risk To The Organization And, Therefore, It Is Expected That Every Person Working For, Or On Behalf Of, Mastercard Is Responsible For Information Security And Must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. #AI3 Corporate Security Responsibility All Activities Involving Access To Mastercard Assets, Information, And Networks Comes With An Inherent Risk To The Organization And, Therefore, It Is Expected That Every Person Working For, Or On Behalf Of, Mastercard Is Responsible For Information Security And Must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Role Definition Manages the development, implementation and support of business analytics initiatives and projects. Responsibilities Identifying, sizing and prioritizing business opportunities for improvement through analytics and Development of Power BI Visuals Managing internal client relations to ensure that project expectations are managed, and fulfilled. Monitoring and communicating key performance metrics and operational challenges. Skill Descriptors Business Statistics: Knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions. Level Extensive Experience: Generates and interprets a wide range of statistical data and reports. Utilizes in-depth knowledge of several statistical tools or applications. Instructs others in statistical concepts and techniques and their application to business. Products and Services: Knowledge of Manufacturing environment and Systems like Oracle, SAP Level Extensive Experience: Develops procedures for product planning, development, and delivery cycles. Promotes understanding of multiple product and service groups and their interdependencies. Microsoft Power Platform Experience Power BI development experience Analytical Thinking: Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems. Level Extensive Experience: Seeks discrepancies and inconsistencies in available information; explains variances. Organizes and prioritizes the sequence of steps to be taken to remedy the situation. Identifies many possible causes for a problem based on prior experience and current research. Quantifies the costs, benefits, risks and chances for success before recommending a course of action. Approaches a complex problem by breaking it down into its component parts. Chooses among a diverse set of analytical tools according to the nature of the situation. Innovation: Knowledge of the value of innovation; ability to create and develop new ideas for answers to work-related problems that improve the performance of the organization. Level Extensive Experience: Finds new or non-traditional ideas to improve effectiveness in team's area of responsibility. Guides team members in the development and fulfilment of proposed innovations. Fosters a team culture that encourages exploration of non-traditional ideas. Encourages and embraces exploration of non-traditional ideas from team members. Implements strategies for renewing or deepening change efforts. Develops change initiatives that target improvement of significant organizational capabilities. Emerging Technologies: Knowledge of emerging technologies; ability to design, apply and evaluate new information technologies for business environments. Level Extensive Experience: Evaluates best practices of emerging information technologies to learn and understand principles and applications. Evaluates business accuracy and productivity levels derived from information technology influences. Determines long-term, strategic requirements for the design of information technologies. Monitors information technology users to ensure compliance with organizational policies. Resolves all technical and administrative problems that occur in the design, application and evaluation of information technology. Machine Learning: Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services. Level Working Knowledge: Completes specific tasks and initiatives utilizing machine learning technologies, such as search engine optimization. Utilizes specific tools and techniques to process descriptive and inferential statistics. Applies specific computing languages and tools in machine learning, such as SQL, and Python. Explores to use machine learning in one own areas to make business improvements. Conducts data mining and cleaning initiatives.