1143 Statistical Modeling Jobs - Page 11

Salary : 25 to 40 LPA Exp: 4 to 8 years Location :/Gurugram/Bangalore/Hyderabad Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Salary : 20 to 35 LPA Exp: 3 to 8 years Location :/Gurugram/Bangalore/Hyderabad Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

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

Job Description The GN SC&O - S&P - I&F Decision Sci Practitioner Sr Analyst is responsible for leveraging data analytics to inform and enhance supply chain decision-making processes. This role requires a strong analytical mindset and the ability to work collaboratively with various teams to drive improvements in inventory management and demand forecasting. Responsibilities Analyze data to support strategic decision-making in supply chain operations. Develop and implement advanced analytics models to optimize inventory and forecast demand. Collaborate with cross-functional teams to gather requirements and deliver actionable insights. Prepare and present analytical reports to stakeholders to drive business performance. Utilize data visualization tools to communicate findings effectively. Skills and Qualifications Bachelor's degree in Data Science, Statistics, Mathematics, or related field. 3-5 years of experience in data analysis, decision science, or supply chain analytics. Proficiency in statistical analysis tools such as R, Python, or SAS. Experience with data visualization tools like Tableau or Power BI. Strong understanding of supply chain processes and metrics. Excellent problem-solving and critical-thinking skills. Effective communication skills to convey complex data insights to non-technical stakeholders.

About Klook Klook is Asia's leading platform for experiences and travel services, dedicated to bringing the world closer together through unique and unforgettable experiences. Founded in 2014 by three passionate travelers - Ethan Lin, Eric Gnock Fah, and Bernie Xiong, Klook offers over half a million curated quality experiences in 2,700 destinations worldwide. From iconic attractions to adventurous activities like paragliding, from cultural tours to convenient local travel services, Klook aims to inspire and enable more moments of joy for travelers around the globe. Do you share our belief in the transformative power of travel Join our international community of over 1,800 employees across 30+ locations who are not only curating memorable experiences but also co-creating a world of joy within Klook. At Klook, we work hard and play hard, maintaining a high-performing culture guided by our six core values: Customer First, Push Boundaries, Critical Thinking, Build for Scale, Less is More, and Win as One. We constantly strive for excellence and believe in reaching greater heights in the ever-evolving travel industry. If you are passionate about travel and innovation, come be a part of our revolution! As a Data Scientist in the Pricing Strategy team, you will be instrumental in driving data-driven decision-making and optimizing pricing strategies. Your role will involve developing and implementing dynamic pricing models, predictive and prescriptive analysis, and contributing to revenue growth and market competitiveness. What You'll Do Dynamic Pricing Model Development: Create and implement advanced dynamic pricing models to optimize product pricing across different channels and markets. Predictive Analytics: Utilize predictive modeling techniques to forecast demand, market trends, and customer behavior for proactive pricing adjustments. Prescriptive Analysis: Use prescriptive analytics to identify optimal pricing strategies aligned with specific business objectives and constraints. Data Exploration and Analysis: Conduct thorough data exploration and analysis to extract valuable insights for informing pricing decisions. Model Evaluation and Refinement: Continuously assess and refine pricing models to ensure accuracy and effectiveness. Collaboration: Work closely with cross-functional teams such as marketing, sales, and finance to align pricing strategies with overall business goals. Stay Updated: Keep abreast of the latest advancements in data science and pricing optimization techniques. What You'll Need Master's degree or PhD in Data Science, Statistics, Computer Science, Economics, or a related field. 3-4 years of relevant experience in Data Science. Proficiency in Python or R for programming, data manipulation, analysis, and visualization using libraries like Pandas, NumPy, Matplotlib, and Seaborn. Knowledge of machine learning algorithms (e.g., regression, classification, clustering, time series analysis) and statistical modeling. Familiarity with data warehousing and cloud computing platforms (e.g., AWS, GCP, Azure) is a plus. Strong problem-solving and analytical skills. Ability to effectively communicate complex technical concepts to both technical and non-technical audiences. Passion for data-driven decision-making and a continuous learning mindset. Klook is committed to being an equal opportunity employer, welcoming talented and passionate individuals from diverse backgrounds. We believe in fostering an inclusive workplace where everyone has an equal opportunity to thrive. Join us in creating a supportive and inclusive culture where every individual belongs.,

The Company Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do and they push us to ensure we take care of ourselves, each other, and our communities. Job Description: Your way to impact Your day to day Build, enhance, and document CECL/IFRS9-compliant loss prediction models, leveraging PD/EAD/LGD frameworks and vintage loss rate methodologies. Conduct rigorous model performance testing, stress testing, and scenario analysis to ensure models are robust and regulatory-compliant. Collaborate cross-functionally with implementation, finance, accounting, risk, and external stakeholders to align on model outputs, definitions, and business needs. Clearly communicate analytic insights and model results to senior leadership, and provide expert support for regulatory exams and audit reviews. What do you need to bring Advanced degree in a quantitative discipline (e.g., statistics, mathematics, data science, computer science, engineering, or related field). Deep expertise in statistical modeling, machine learning, or econometrics applied to credit risk, knowledge and familiarity of CECL and IFRS9 regulatory requirements and modeling best practices is a plus. Strong technical skills working with large datasets using SQL, Python, R, or similar tools; experience with cloud-based platforms such as GCP is highly desirable. 5+ years of hands-on experience developing consumer or small business credit risk models, preferably within a CECL/IFRS9 framework. Excellent communication and collaboration skills, with strong business judgment and a passion for data-driven problem solving. Our Benefits: Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.,

As a Member Technical Staff I at Adobe, you will be an integral part of our engineering team in Bengaluru, collaborating with a talented group to work on impactful global projects. Your role involves developing and programming software algorithms to analyze and utilize data effectively in various environments. You will be responsible for communicating insights and algorithms clearly, employing machine learning and statistical modeling techniques to enhance system performance, and translating technical specifications into efficient code using current programming languages. Testing, debugging, and ensuring software quality are crucial aspects of your responsibilities, along with documenting installation and maintenance procedures for developed systems. Additionally, you will apply deep learning technologies to enable computers to understand and respond to complex scenarios and adapt machine learning to interactive products such as virtual reality, augmented reality, and robotics. Your qualifications should include proven experience in software algorithm development, a strong grasp of machine learning and deep learning technologies, proficiency in programming languages, and the ability to work with large-scale computing frameworks and data analysis systems. If you are a problem-solver with attention to detail, excellent communication skills, and the ability to collaborate effectively in a team-oriented environment, we invite you to join Adobe. Be part of a team dedicated to shaping the future of digital experiences and contributing to innovative projects that make a difference globally.,

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. In this role, you will play a key role in delivering key insights from corporate data sources to support planning and operations of the Sourcing, Procurement, and Third Party Risk teams, which sit within the Finance organization. You will develop reports and dashboard tools to visualize data for rapid and clear understanding and communication. Additionally, you will work with business partners to understand data requirements and implement processes for ensuring data integrity. Role Objectives - Create effective data visualizations/dashboards utilizing Power BI - Employ an understanding of statistical modeling and analysis frameworks to gain key insights from collected data and support the development of predictive data models - Perform initial clean-up and classification of datasets, apply transformations to ensure compliance with data dictionaries, source missing data, and trace the origin of any data quality issues. Your Profile - Maintain and run queries against corporate datasets to answer key business questions - Support exploratory analysis of existing data to uncover new trends and insights - Troubleshoot issues with reports and dashboards to enable continuous monitoring of important business performance metrics and support effective visualization of data - Work with Sourcing, Procurement, and Risk leadership and other business teams to develop key data questions and performance metrics - Establish your position as a resource to colleagues for advice on all aspects of data utilization, including capture, analysis, reporting, and prediction - Assist in delivering advice to business partners on data capture requirements for analysis and on the creation of metrics to capture performance insights Capgemini is a global business and technology transformation partner, helping organizations accelerate their dual transition to a digital and sustainable world while creating tangible impact for enterprises and society. With a responsible and diverse group of 340,000 team members in more than 50 countries, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. The company delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market-leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.,

You are an experienced Lead Model Developer/Validator with a strong background in credit risk modeling, particularly focusing on Internal Credit Risk Rating modeling. Your main responsibility will involve leading the development and validation of advanced credit risk models, including PD, EAD, LGD, with a special emphasis on Expert judgment-based PD models for Corporate, Specialized Lending, and Financial Institutions. Your role will require you to conduct thorough data preparation and preprocessing using tools such as SAS, Python, R, and SQL. You will collaborate with various stakeholders to analyze, interpret, and communicate complex model results and insights. Additionally, you will be responsible for creating technical documentation including regulatory compliance model documentation, test plans, validation reports, findings report, and business requirements documents where applicable. Continuous improvement of models will be a key aspect of your job, involving identifying optimization opportunities, implementing advanced modeling techniques, and enhancing model performance and predictive accuracy. Moreover, you will be expected to provide mentorship and technical guidance to junior team members, promoting a culture of knowledge sharing and professional development. To qualify for this position, you should have 5-10 years of hands-on experience in credit risk model development and validation, proven expertise in modeling across retail and wholesale credit portfolios, and advanced proficiency in SAS, Python, R, and SQL. A deep understanding of IFRS9 and CECL regulatory frameworks and guidance, exceptional analytical and problem-solving skills, as well as excellent written and verbal communication abilities are essential. Preferred qualifications include an advanced degree in Statistics, Mathematics, Economics, or a related field, professional certifications in risk management or financial modeling, experience with IRB modeling, machine learning/advanced statistical modeling techniques, and knowledge of Basel regulatory guidance. Your technical skills should encompass model development (PD, LGD, EAD, Qualitative PD Models), programming (SAS, Python, R, SQL), regulatory knowledge (IRB, IFRS9, CECL), statistical modeling, data preprocessing, and machine learning techniques. If you meet these qualifications and are looking for a challenging opportunity to leverage your expertise in credit risk modeling, this role offers a platform to lead and drive sophisticated credit risk modeling initiatives across various portfolios.,

Job Description: Key Responsibilities **Text Embeddings & NLP** -Must have 3+ Years of experience on traditional ML. -Must have 3+ Years of experience working as Data scientist. Design and implement pipelines leveraging text embeddings for semantic search, classification, clustering, and document retrieval. - Work with embedding techniques such as TF-IDF, Word2Vec, GloVe, FastText, and transformer-based models including BERT, Sentence-BERT, OpenAI, and Azure OpenAI embeddings. - Apply dimensionality reduction methods (PCA, t-SNE, UMAP) to analyze and visualize embedding spaces. - Use cosine similarity, Euclidean distance, and approximate nearest neighbor algorithms like FAISS and ScaNN for similarity search and clustering. - Integrate embedding outputs into downstream applications such as intent detection, topic modeling, semantic deduplication, document ranking, and retrieval systems. **Traditional Machine Learning & Statistical Modeling** - Build and deploy predictive models with logistic/linear regression, random forests, gradient boosting techniques (XGBoost, LightGBM), SVM, Naive Bayes, k-means, and hierarchical clustering. - Employ statistical inference techniques including hypothesis testing, confidence intervals, bootstrapping, Bayesian inference, multicollinearity diagnostics, residual analysis, and time series forecasting (ARIMA, SARIMA). - Evaluate model performance using ROC/Precision-Recall curves, AUC, confusion matrices, F1-score, lift/gain charts, and KS statistics. - Conduct feature selection via Lasso/Ridge regression, recursive feature elimination (RFE), and SHAP values for interpretability. **Experimentation & Causal Inference** - Design and analyze A/B and multivariate tests, DOE experiments, and sophisticated causal inference methods including propensity score matching, causal forests, and difference-in-differences. - Translate experimental results into clear, actionable business insights that drive measurable outcomes. **Data Engineering & Productionization** - Develop scalable data pipelines using PySpark, SQL, and Azure Data Factory on platforms including Azure Data Lake, Databricks, MongoDB, and Cosmos DB. - Deploy machine learning solutions with FastAPI, Docker containers, and Azure App Services endpoints, while monitoring model health with MLflow and model drift. **Collaboration & Leadership** - Partner effectively with engineering, product, and business teams to define problem statements and deliver impactful solutions. - Lead technical discussions, perform code reviews, and mentor junior data scientists to foster technical growth. - Communicate complex analytical insights clearly to both technical and non-technical stakeholders. Required Skills and Qualifications Hands-on experience in machine learning, statistical modeling, and NLP applications. - Deep expertise in text embeddings and their real-world applications. - Proficiency in Python, PySpark, and SQL. - Strong foundation in statistical inference, model diagnostics, and evaluation metrics. - Experience working with Azure cloud ecosystem, Databricks, and production deployment of ML models. - Proven ability to design, execute, and interpret experiments with statistical rigor. Preferred (Good-to-Have) Skills - Familiarity with transformer-based large language models (LLMs), LangChain, or OpenAI APIs. - Experience with MLOps tools such as MLflow and Github Actions CI/CD pipelines with Azure App Services. - Exposure to graph analytics, retrieval-augmented generation (RAG) pipelines, or agent-based systems. Day-to-Day Responsibilities You will architect and implement advanced NLP and machine learning pipelines leveraging diverse text embeddings for semantic search, classification, and clustering tasks. Applying sound statistical modeling and causal inference techniques, you will lead experimentation efforts and build scalable data workflows using PySpark, SQL, and Azure services. Cross-functional collaboration will be a core part of your role as you translate analytical insights into strategic business outcomes.

Assistant General Manager - Customer Delight: Job Summary: We arelooking for a dynamic and experienced Assistant General Manager (AGM) Customer Delight to lead and oversee large-scale contact centre operationsacross multiple processes. This role demands strong leadership, strategicvision, and operational expertise to drive superior customer service, enhancecustomer satisfaction, and optimize operational efficiencies across diverseteams and service channels. Key Responsibilities: Strategic Leadership & Operational Oversight: Provide leadership and direction for large contact centre operations involving multiple teams and processes, ensuring alignment with company goals and customer experience strategies. Should have managed more than 150+ FTEs spread across multiple processes/contact centres. Multi-Process Management: Oversee the delivery of multiple customer service processes (e.g., inbound/outbound calls, chat, email, social media support), ensuring consistent service quality and performance standards across channels. Team Management & Development: Manage, mentor, and motivate a large workforce including team leads, supervisors, and agents. Drive talent acquisition, training, succession planning, and career development programs. Performance Management & Analytics: Define and monitor comprehensive KPIs such as Customer Satisfaction (CSAT), Net Promoter Score (NPS), Average Handle Time (AHT), First Contact Resolution (FCR), and Service Level Agreements (SLAs). Utilize data analytics to identify trends, optimize workflows, and drive continuous improvements. Process Optimization & Innovation: Lead initiatives to streamline processes, improve operational efficiency, and enhance the customer journey through automation, technology upgrades, and best practices. Customer Escalations & Quality Assurance: Handle escalated customer issues promptly, ensuring effective resolution and maintaining customer trust. Oversee quality assurance programs to maintain high service standards. Budget & Resource Management: Develop and manage operational budgets, resource planning, and vendor relationships to support scalable and cost-effective contact centre operations. Compliance & Risk Management: Ensure all operations comply with regulatory requirements, data privacy laws, and company policies. Lead risk mitigation and business continuity planning. Cross-Functional Collaboration: Work closely with other departments such as IT, Sales, Marketing, and Product teams to align customer experience initiatives and resolve systemic issues impacting customer satisfaction. Automation and AI deployment Ensuring the right deployment of AI solutions which results in the overall contacts volume reduction and increased efficiency as well as the quality of service. Qualifications & Experience: Bachelors degree in Business Administration, Management, or related field; MBA or advanced degree preferred. Minimum 10 years of progressive experience in contact centre management or customer experience leadership roles. Proven experience managing large teams (100+ employees) across multiple processes in a complex contact centre environment. Strong strategic thinking, analytical skills, and data-driven decision-making abilities. Excellent leadership, communication, and interpersonal skills. Proficient in CRM platforms, workforce management, and contact centre technologies. Demonstrated ability to drive transformation and deliver results in fast-paced, high-pressure environments. Key Competencies: Strategic leadership & vision Multi-channel customer service expertise Large team & multi-process management Operational excellence & process improvement Data analytics & performance management Stakeholder management & collaboration Change management & innovation mindset

Position level: AI Specialist/Software engineering professional (Cant be a junior/fresher, needs to be middle to senior level person) Work Experience: Ideally, 4 to 5 years of working as a Data Scientist / Machine Learning and AI at a managerial position (end-to-end project responsibility). Slightly lower work experience can be considered based on the skill level of the candidate. About the job: Use AI-ML to work with data to predict process behaviors. Stay abreast of industry trends, emerging technologies, and best practices in data science, and provide recommendations for adopting innovative approaches within the product teams. In addition, championing a data-driven culture, promoting best practices, knowledge sharing, and collaborative problem-solving. Abilities: Knowledge about data analysis, Artificial Intelligence (AI), Machine Learning (ML), and preparation of test reports to show results of tests. Strong in communication with a collaborative attitude, not afraid to take responsibility and make decisions, open to new learning, and adapt. Experience with end-to-end process and used to make result presentation to customers. Technical Requirements: Experience working with real world messy data (time series, sensors, etc.) Familiarity with Machine learning and statistical modelling Ability to interpret model results in business context Knowledge of Data preprocessing (feature engineering, outlier handling, etc.) Soft Skill Requirements: Analytical thinking Ability to connect results to business or process understanding Communication skills Comfortable explaining complex topics to stakeholders Structured problem solving – Able to define and execute a structured way to reach results Autonomous working style – can drive a small project or parts of a project Tool Knowledge: Programming: Python (Common core libraries: pandas, numpy, scikit-learn, matplotlib, mlfow etc.); Knowledge of best practices (PEP8, code structure, testing, etc.) Code versioning (GIT) Data Handling: SQL; Understanding of data format (CSV, JSON, Parquet); Familiarity with time series data handling Infrastructure: Basic Cloud technology knowledge (Azure (preferred), AWS, GCP); Basic Knowledge of MLOps workflow Good to have: Knowledge of Azure ML, AWS SageMaker; Knowledge of MLOps best practices in any tool; Containerization and deployment (Docker, Kubernetes) Languages: English – Proficient/Fluent Location: Hybrid (WFO+WFH) + Availability to visit customer sites for meetings and work-related responsibilities as per the project requirement.

We are looking for a Data Scientist who will support building AI tools for customers The candidate should be skilled at using large data sets to find opportunities for product and process optimization The candidate must have a proven ability to drive business results with their databased insights The candidate must be comfortable working with a wide range of stakeholders and functional teams Primary Skills Python, AI, ML (Machine Learning) Gen AI Generative AI + RAG, NLP, LLM, Deep Learning, Computer Vision, AWS, Cloud Or Azure Open AI (Any Cloud) Experience- 5 to 16 Years Location - Pune If anyone is interested please share your updated resume on my email id - Devyani.Pillai2@ltimindtree.com

ECMS # 527228 Number of Openings 2 Duration of project 6 months will get extended No of years experience Total - 10+ Yrs exp Relevant experience 6+ yrs in Data Scientist Detailed job description - Skill Set: Data Scientist (10+ Years Experience) Job Title: Data Scientist / Senior Data Scientist Location: Bangalore / Hyderabad (should be able to come in to office 5 days / week) Job Summary: As a Data Scientist, you will design and implement machine learning models and advanced analytics solutions to solve complex business problems. You will work with large-scale data, build predictive models, and collaborate with engineering and product teams to deploy data-driven solutions. You will also lead initiatives in computer vision and deploy models using AWS services . Key Responsibilities: Develop and deploy machine learning models for classification, regression, clustering, and recommendation systems. Design and implement computer vision solutions using CNNs, object detection, and image segmentation techniques. Deploy machine learning models using AWS services such as SageMaker, Lambda, S3, and API Gateway. Perform feature engineering, model selection, and hyperparameter tuning. Analyze experimental results and iterate on model improvements. Collaborate with data engineers to ensure data pipelines are robust and scalable. Communicate technical findings to non-technical stakeholders. Stay updated with the latest research and trends in data science and AI. Required Skills & Qualifications: Masters or PhD in Computer Science, Statistics, Mathematics, or a related field. Strong programming skills in Python (pandas, scikit-learn, TensorFlow, PyTorch). Solid understanding of machine learning algorithms and statistical modeling. Hands-on experience with computer vision libraries such as OpenCV, TensorFlow, or PyTorch. Experience deploying models on AWS using services like SageMaker, Lambda, and S3. Familiarity with big data tools (e. g. , Spark, Hadoop) and cloud platforms. Proficiency in SQL and data wrangling. Strong communication and collaboration skills. Mandatory Skills Data Scientist with Strong hands on skills in AI, ML models , computer Vision solutions, AWS Services , Python , Data Pipeline. Vendor Billing range (local currency /Day) 11500 INR per day Work Location Bangalore / Hyd Client office all 5 days resource need to work at client location Hybrid/Remote/WFO No BGV Pre/Post onboarding Pre Any particular shift timings No

Position Overview : We are seeking a skilled Statistical Programmer to join our clinical research team. The successful candidate will be responsible for programming, validating, and delivering statistical outputs for clinical trials while ensuring compliance with regulatory standards and industry best practices. Key Responsibilities : Programming & Data Management : - Develop and maintain SAS programs for clinical trial data processing, analysis, and reporting. - Map clinical trial data to CDISC standards (SDTM and ADaM) ensuring compliance with regulatory requirements. - Create and maintain analysis datasets following CDISC implementation guidelines. - Perform data validation and quality control checks to ensure data integrity. Documentation & Compliance : - Generate and maintain CDISC documentation including define.xml files, reviewer's guides, and annotated case report forms (aCRF). - Conduct Pinnacle21 validation checks and resolve any compliance issues. - Ensure all deliverables meet regulatory submission standards (FDA, EMA, etc.). - Maintain comprehensive programming documentation and version control. Statistical Analysis & Reporting : - Produce Tables, Listings, and Figures (TLFs) based on Statistical Analysis Plans (SAP). - Collaborate with biostatisticians to implement complex statistical analyses. - Support clinical study reports and regulatory submissions. - Perform ad-hoc analyses as requested by clinical teams. Cross-functional Collaboration : - Work closely with clinical data management, biostatistics, and regulatory affairs teams. - Participate in project meetings and provide technical expertise. - Support timeline planning and deliverable tracking. - Mentor junior programmers and provide technical guidance. Required Qualifications : Technical Skills : - Minimum 3+ years of experience as a statistical programmer in clinical research or pharmaceutical industry. - Advanced SAS programming skills with expertise in Base SAS, SAS/STAT, SAS/GRAPH, and SAS Macro language. - Strong understanding of clinical trials including study designs, endpoints, and regulatory requirements. - Proven experience with CDISC standards (SDTM and ADaM) and data mapping techniques. - Experience with CDISC documentation including define.xml, reviewer's guides, and aCRF preparation. - Hands-on experience with Pinnacle21 validation software and resolving compliance issues. - Demonstrated ability to produce TLFs based on Statistical Analysis Plans with attention to detail. Soft Skills : - Fluent in English with excellent written and verbal communication skills. - Strong problem-solving mentality with ability to troubleshoot complex technical issues. - Detail-oriented approach with commitment to accuracy and quality. - Excellent communication and interpersonal skills for effective team collaboration. - Fast learner with ability to adapt to new technologies and methodologies. - Strong organizational skills and ability to manage multiple priorities. Preferred Qualifications (Nice to Have) : - Real-World Data (RWD) experience including analysis of electronic health records, claims data, or registries. - Pharmacokinetic (PK) calculations experience and understanding of PK/PD modeling. - R programming skills for statistical analysis and data visualization. - Experience with other statistical software packages (Python, SPSS, etc.). - Knowledge of therapeutic areas and regulatory guidelines. - Experience with cloud-based platforms and version control systems. Education Requirements : - Bachelor's degree in Statistics, Mathematics, Computer Science, Life Sciences, or related field. - Advanced degree preferred but not required with relevant experience. This position offers an excellent opportunity for a skilled statistical programmer to contribute to meaningful clinical research while developing expertise in regulatory compliance and industry best practices.

Job Role: - Candidate should know end to end working and functioning of payment products viz. IMPS, UPI, RTGS, NEFT and cards and have demonstrated building analytics driven solutions to prevent frauds - Knowledge of Fraud management platforms is preferred - Responsible to Review Fraud trends across Digital and Cards payments and Implement Rules to detect and prevent frauds - Working knowledge of rule writing in FRMs like Falcon and Clari5 is required - Candidate has demonstrated experience in building credit risk models for Credit Cards using various Statistical models and Machine Learning models - Coding knowledge on Hadoop environment is added advantage - Should be able to work in minimum supervision Skills required: Building predictive Models/Machine Learning models and managing big data using Python and SAS is must. Education : M Tech/B Tech/Statistics degree is mandatory Location: Mumbai Presentation: Good written and verbal communication skills Prior experience in Analytics with BFSI for 2-3 years is a must Hands -on experience on following methods and techniques is required as role involves working with both structure and unstructured data Network Analysis(Graph theory) Link Analysis ( Market Basket/Sequence Analysis) Text mining & NLP Regressions ( eg. Logistic ) Classification methods (Decision Tree, Neural Networks, KNN, SVM) Anomaly detection methods

We are seeking an Analyst III Business Process Transactions to join our team in India. The ideal candidate will play a key role in analyzing and improving business processes and transactions to enhance efficiency and effectiveness. Responsibilities Analyze business processes and transactions to identify areas for improvement. Support the development and implementation of process improvement initiatives. Collaborate with cross-functional teams to gather requirements and provide insights. Generate reports and dashboards to track performance metrics and KPIs. Assist in preparing documentation related to business processes and transaction workflows. Skills and Qualifications Bachelor's degree in Business Administration, Finance, or a related field. Proficient in data analysis tools such as Excel, SQL, and data visualization software. Strong analytical and problem-solving skills. Excellent communication and interpersonal skills. Ability to work collaboratively in a team environment. Knowledge of business process modeling techniques and methodologies.

Join this dynamic Quant profile to contribute to the Global Markets Planning & Analysis Group, with teams located in New York, London, and Mumbai, while being stationed at Corporate and Investment Banking Research & Analytics in Mumbai. As an Associate within the Modeling Center of Excellence team, you will be working in a team of roughly 25 individuals and be responsible for the design, engineering, industrialization and support of the Quantitative Framework for the CCAR/ICAAP regulatory process, while also exploring opportunities to further leverage it into other activities such as the planning and forecast processes, ad hoc analysis for senior management and other strategic initiatives to support the businesses. The team is based out of L&T office of J.P. Morgan in Powai, Mumbai. You will need to work closely with stakeholders in London and New York, partnering and supporting them just as a direct extension of the team sitting out of Mumbai. You will also be able to interact with JPMorgans Quantitative Research team in Mumbai and benefit from their experience. Job Responsibilities: - Perform in-depth data analysis, using statistical and machine learning modeling techniques (regression, decision tree, ECM, neural networks, regime switching, etc.), to creatively build predictive or explanatory models - Devise/improve models on new/existing regression models. This includes coding the entire statistical methodology in R, Python - Translate business needs into quantitative analyses and tools; communicate complex results to senior stakeholders in a clear and precise manner - Work independently and collaboratively to establish close partnerships with peers across the greater CIB organization and Global Treasury. - Develop metrics and statistical model prototypes that can be used to drive business decisions. - Lead and participate in ad-hoc projects as needed by senior management or regulatory initiatives - Clearly document the code of the tools created; Publish and maintain clear user documentation; Write the official Model documentation and interact with the Model Governance group for review and approval; Ensure full SIT / UAT and Change controls of tools Required Qualifications, Skills and Capabilities: - Experience of working on Python/R statistical, analytical and machine learning libraries. - Experience of working on probability theory, statistics and machine learning. - Close attention to detail and ability to work to very high standards - Strong quantitative and analytical skills - Strong communication skills (both written and verbal) and ability to present findings to a non-technical audience - Candidates for these positions should be graduates/post-graduates with good academic records from esteemed universities with some exposure to finance/actuaries/accounting and/or derivatives. - Strong knowledge of Equities, FX, Rates, Fixed Income or Commodities,

Data scientists at Thoughtworks are responsible for leading and executing data science projects. They employ their profound expertise in statistics, modeling, machine learning algorithms and data mining methodologies. They integrate this expertise with a comprehensive understanding of related domains to render business value and illuminate data-driven insights, facilitating clear and effective decision-making processes. Their responsibilities encompass devising strategies, executing plans, operationalizing solutions and articulating the tangible business outcomes achieved. Collaborating with cross-functional teams is pivotal, as they adeptly convey their discoveries to both technical and non-technical stakeholders. They stay up-to-date with industry advancements, ensure data quality and security, and provide guidance to junior team members. As a data scientist at Thoughtworks, you'll work on a range of projects and leverage deep technical knowledge to solve complex business problems. Job responsibilities You will lead and manage data science projects from inception to completion, including goal-setting, scope definition and ensuring on-time delivery with cross team collaboration You will collaborate with stakeholders to understand their strategic objectives and identify opportunities to leverage data and data quality for enabling AI and machine learning You will be responsible for the overall AI system design, problem framing and governance, identifying and managing risks and issues You will design, develop and implement data science strategies that drive measurable business results You will design experiments for the team to rapidly test ideas and assumptions, and identify future courses of action You will use quality metrics to select machine learning models that will be deployed in the production environment You will communicate technical findings and insights to stakeholders in a clear, easy and concise way, keeping the stakeholders in mind You will contribute to the growth of the data science community along with promoting a culture of data literacy within the organization You will address ethical concerns and adhere to ethical guidelines using FATTER AI (fairness, accountability, transparency, trustworthiness, explainability, responsibility) You will work with CD4ML practices and data versioning tools Job qualifications Technical Skills You have experience in leading the analysis and modeling of different datasets and overseeing an inception to deploying and productionizing the models You have experience with statistical modeling, hypothesis testing, machine learning, deep learning, optimization and other data science techniques to implement end-to-end data science projects You understand the specialized areas of AI and possess a speciality with at least one of them (i.e.: NLP/computer vision/Generative AI, etc)tc) You have experience with R, Python or equivalent statistical/data analysis tools and can write production-ready code that is easy to evolve and test You gather and preprocess large volumes of structured and unstructured data from various sources, ensuring data quality and integrity You analyze datasets using statistical and visualization techniques to identify patterns, trends and relationships You develop and implement machine learning models, algorithms and predictive analytics to solve specific business problems or improve existing processes You evaluate model performance using appropriate metrics and validate models to ensure robustness and reliability You interpret and effectively communicate findings and insights to non-technical stakeholders through reports, presentations and visualizations You ensure compliance with data privacy regulations and ethical standards when handling sensitive information Professional Skills You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives You dont shy away from risks or conflicts, instead you take them on and skillfully manage them You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work You enjoy influencing others and always advocate for technical excellence while being open to change when needed You are a proven leader with a track record of encouraging teammates in their professional development and relationships Cultivating strong partnerships comes naturally to you; You understand the importance of relationship building and how it can bring new opportunities to our business

upstox is looking for Data Science Intern to join our dynamic team and embark on a rewarding career journey Assist in data science projects and activities Conduct data analysis and visualization Develop and implement data science models and algorithms Monitor and report on data science performance metrics Collaborate with data science teams to optimize operations Gain practical experience in data science

Summary:We are seeking an experienced Data Scientist to join our team at Test Demo in Chennai As a Data Scientist with 4 years of experience, you will play a key role in driving business growth through data-driven insights and recommendations This is an in-office role, and we are looking for someone who is passionate about working with data and has a strong analytical mindset As a Data Scientist at Test Demo, you will be responsible for collecting, analyzing, and interpreting large data sets to identify trends and patterns You will work closely with cross-functional teams to develop and implement data-driven solutions that drive business outcomes Your expertise in machine learning, statistical modeling, and data visualization will be essential in helping us make informed business decisions The ideal candidate will have a strong foundation in computer science, statistics, and mathematics, with experience working with programming languages such as Python, R, or SQL You will be expected to have a strong understanding of data structures, algorithms, and data modeling techniques At Test Demo, we offer a collaborative and supportive work environment that fosters growth and learning Join our team in Chennai and be a part of our mission to drive innovation through data science ResponsibilitiesCollecting, analyzing, and interpreting large data sets to identify trends and patternsWorking closely with cross-functional teams to develop and implement data-driven solutions that drive business outcomesApplying expertise in machine learning, statistical modeling, and data visualization to help make informed business decisionsDesigning and implementing data models, algorithms, and data structures to solve complex business problemsCommunicating insights and recommendations to stakeholders through clear and actionable reports and presentationsRequirements4 years of experience in Data ScienceStrong foundation in computer science, statistics, and mathematicsExperience working with programming languages such as Python, R, or SQLStrong understanding of data structures, algorithms, and data modeling techniques

Data scientists at Thoughtworks apply a deep knowledge of statistics, modeling, machine learning algorithms and data mining techniques. This is coupled with awareness of adjacent areas, to make business value and data insights visible, enabling clear and effective decision making. They are responsible for the strategy, implementation, productionization and articulation of business impact. They collaborate with cross-functional teams and communicate findings to both technical and non-technical stakeholders. They stay up-to-date with industry advancements, ensure data quality and security, and provide guidance to junior team members. As a data scientist at Thoughtworks, you'll work on a range of projects and leverage deep technical knowledge to solve complex business problems. Job responsibilities You will work collaboratively with teams/products, crafting data science and machine learning solutions that generate a big impact on customers You will conduct experiments and develop hypotheses to solve business problems using advanced statistics techniques You will develop and implement data science strategies that drive measurable business results You will communicate technical findings and insights to stakeholders in a clear, easy and concise way, keeping the stakeholders in mind You will interact with clients from diverse domains, addressing their challenging problems You will contribute to the growth and knowledge sharing within the data science community, with a focus on latest tech trends in the data science and machine learning space You will address ethical concerns in data science, including privacy, bias and fairness, while adhering to ethical guidelines Job qualifications Technical Skills You have experience with statistical modeling, machine learning, deep learning, optimization and other data science techniques to implement end-to-end data science projects You understand the specialized areas of AI and possess experience with at least one of them (i.e.: NLP/computer vision/Generative AI, etc) You have experience with R, Python or equivalent statistical/data analysis tools and can write production-ready code that is easy to evolve and test You gather and preprocess large volumes of structured and unstructured data from various sources, ensuring data quality and integrity You analyze datasets using statistical and visualization techniques to identify patterns, trends and relationships You develop and implement machine learning models, algorithms and predictive analytics to solve specific business problems or improve existing processes You evaluate model performance using appropriate metrics and validate models to ensure robustness and reliability You interpret and effectively communicate findings and insights to non-technical stakeholders through reports, presentations and visualizations You are aware of data privacy regulations and ethical standards when handling sensitive information Professional Skills You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives You dont shy away from risks or conflicts, instead you take them on and skillfully manage them You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work You enjoy influencing others and always advocate for technical excellence while being open to change when needed

Introduction to the Role: Are you passionate about building intelligent systems that learn, adapt, and deliver real-world value? Join our high-impact AI & Machine Learning Engineering team and be a key contributor in shaping the next generation of intelligent applications. As an AI/ML Engineer , youll have the unique opportunity to develop, deploy, and scale advanced ML and Generative AI (GenAI) solutions in production environments, leveraging cutting-edge technologies, frameworks, and cloud platforms . In this role, you will collaborate with cross-functional teams including data engineers, product managers, MLOps engineers, and architects to design and implement production-grade AI solutions across domains. If you're looking to work at the intersection of deep learning, GenAI, cloud computing, and MLOps this is the role for you. Accountabilities: Design, develop, train, and deploy production-grade ML and GenAI models across use cases including NLP, computer vision, and structured data modeling. Leverage frameworks such as TensorFlow , Keras , PyTorch , and LangChain to build scalable deep learning and LLM-based solutions. Develop and maintain end-to-end ML pipelines with reusable, modular components for data ingestion, feature engineering, model training, and deployment. Implement and manage models on cloud platforms such as AWS , GCP , or Azure using services like SageMaker , Vertex AI , or Azure ML . Apply MLOps best practices using tools like MLflow , Kubeflow , Weights & Biases , Airflow , DVC , and Prefect to ensure scalable and reliable ML delivery. Incorporate CI/CD pipelines (using Jenkins, GitHub Actions, or similar) to automate testing, packaging, and deployment of ML workloads. Containerize applications using Docker and orchestrate scalable deployments via Kubernetes . Integrate LLMs with APIs and external systems using LangChain, Vector Databases (e.g., FAISS, Pinecone), and prompt engineering best practices. Collaborate closely with data engineers to access, prepare, and transform large-scale structured and unstructured datasets for ML pipelines. Build monitoring and retraining workflows to ensure models remain performant and robust in production. Evaluate and integrate third-party GenAI APIs or foundational models where appropriate to accelerate delivery. Maintain rigorous experiment tracking, hyperparameter tuning, and model versioning. Champion industry standards and evolving practices in ML lifecycle management , cloud-native AI architectures , and responsible AI. Work across global, multi-functional teams, including architects, principal engineers, and domain experts. Essential Skills / Experience: 4-7 years of hands-on experience in developing, training, and deploying ML/DL/GenAI models . Strong programming expertise in Python with proficiency in machine learning , data manipulation , and scripting . Demonstrated experience working with Generative AI models and Large Language Models (LLMs) such as GPT, LLaMA, Claude, or similar. Hands-on experience with deep learning frameworks like TensorFlow , Keras , or PyTorch . Experience in LangChain or similar frameworks for LLM-based app orchestration. Proven ability to implement and scale CI/CD pipelines for ML workflows using tools like Jenkins , GitHub , GitLab , or Bitbucket Pipelines . Familiarity with containerization (Docker) and orchestration tools like Kubernetes . Experience working with cloud platforms (AWS, Azure, GCP) and relevant AI/ML services such as SageMaker , Vertex AI , or Azure ML Studio . Knowledge of MLOps tools such as MLflow , Kubeflow , DVC , Weights & Biases , Airflow , and Prefect . Strong understanding of data engineering concepts , including batch/streaming pipelines, data lakes, and real-time processing (e.g., Kafka ). Solid grasp of statistical modeling , machine learning algorithms , and evaluation metrics. Experience with version control systems (Git) and collaborative development workflows. Ability to translate complex business needs into scalable ML architectures and systems. Desirable Skills / Experience: Working knowledge of vector databases (e.g., FAISS , Pinecone , Weaviate ) and semantic search implementation. Hands-on experience with prompt engineering , fine-tuning LLMs, or using techniques like LoRA , PEFT , RLHF . Familiarity with data governance , privacy , and responsible AI guidelines (bias detection, explainability, etc.). Certifications in AWS, Azure, GCP, or ML/AI specializations. Experience in high-compliance industries like pharma , banking , or healthcare . Familiarity with agile methodologies and working in iterative, sprint-based teams. Work Environment & Collaboration: You will be a key member of an agile, forward-thinking AI/ML team that values curiosity, excellence, and impact. Our hybrid work culture promotes flexibility while encouraging regular in-person collaboration to foster innovation and team synergy. You'll have access to the latest technologies, mentorship, and continuous learning opportunities through hands-on projects and professional development resources.

Roles and Responsibilities Design industry metrics to be used real time by the market leaders, cutting across the entire eco-system for all the high growth market, newer applications, cutting edge technology developments impacting main stream businesses Exhibit thought leadership in a domain or business. Building a global industry network. Improvise the quality of research and consulting projects, by adding more insight, accuracy, best practices, domain knowledge and use of advanced metrics. Come out strongly as Industry thought leader and promote yourself through global conferences and proactively commenting on market dynamics by networking with key industry participants globally. Accountable for the P&L of the Respective Business Unit. Demonstrated ability to synthesize and distill the results of complex market research and analytics, resolve complex analytical problems Provide pre sales support to maximize revenues of the end customers and acquire new customers by unique value prop. Managing the delivery of training and development program. Desired Candidate Profile 9-12 years minimum experience in Research and Consulting industry. Strong business development and program management experience in the professional services and solutions arena. Strong quantitative, research, and data analytic skills Hands-on experience in Forecasting, Market research, analytics, Competitive Intelligence, market forecast, syndicated report, corporate strategy, Project Management/Planning, Consulting, Strategic Advisory Experience in an extremely fast paced work environment preferably in research, consulting or marketing/strategy. Strong analytic skills, critical thinking skills with experience in statistical modeling and analysis Exceptional written, oral, and presentation communication abilities Expertise with Excel, PowerPoint. Good People Management skills Ability to work across multiple accounts and projects concurrently, while maintaining the highest level of quality in work Contribute to the achievement of revenue targets by managing the effective and timely delivery of project work.

Position Summary MetLife established a Global capability center (MGCC) in India to scale and mature Data & Analytics, technology and operations capabilities in a cost-effective manner and make MetLife future ready. The center is integral to Global Technology and Operations with a with a focus to protect & build MetLife IP, promote reusability and drive experimentation and innovation. The Data & Analytics team in India mirrors the Global D&A team with an objective to drive business value through trusted data, scaled capabilities, and actionable insights. The operating models consists of business aligned data officers- US, Japan and LatAm & Corporate functions enabled by enterprise COEs- data engineering, data governance and data science. Role Value Proposition: We are looking for you: high performing data and analytics professional - driven by passion and purpose, to drive quality standards and support end-to-end development of actionable, high-impact AI solutions for MetLifes enterprise functions and lines of businesses across markets. This position requires hands-on experience of developing an end-to-end Machine Learning/AI solution that can be leveraged for maximum business impact through on prem /cloud in both real time and batch mode depending upon business requirements. The role would collaborate with multiple stakeholders under the guidance of Lead/Director Data scientists to develop robust, stable, and scalable advanced analytics/machine learning solutions leveraging new age methodologies/techniques. Superior problem-solving ability, curiosity, strong coding skills and attention to detail are the key success factors. Job Responsibilities Expert-level proficiency in at least one statistical tool language (R, Python) with a strong preference towards Python with excellent debugging skills Strong conceptual understanding of machine learning algorithms including linear regressions, classification algorithms, time series techniques, topic modeling etc. Good written, oral communication with ability to communicate effectively with stakeholders Basic to mid-level understanding of the insurance risk selection, underwriting practices and experience in analyzing the insurance portfolios is a plus Mentoring skills are considered as a plus Experience with Big Data platforms Hadoop (Hive, Pig, Map Reduce, HQL)/Spark/H2O-Linux environment is considered as a plus Experience in technologies like Azure and advanced analytics concepts like Simulation, Deep Learning etc. are considered as a plus Knowledge, Skills and Abilities Bachelors degree in a quantitative field required; Masters or PHD preferred 5-8 years of experience in insurance analytics, data science or similar function Work with Lead Data Scientist to translate given business problem into analytical use-cases with defined outcomes Collaborate with Data Scientists to develop, implement and test most appropriate algorithms for a given use-case; be able to review the work of data scientists and provide guidance Translate statistical analysis to insights and recommendations and work with Data Engineers to automate / production Alize them Ensure coding standards as well as designing standards to ensure reusability Drive innovation by enhancing existing solutions and designing new ones Build collaboration and awareness in the global analytics community