143 Statistical Techniques Jobs - Page 2

As a Senior Analyst - Data Analytics, you will leverage your 3+ years of experience in Data Analytics and reporting to design and build interactive dashboards and reports using Power BI and Microsoft Fabric. Your strong technical expertise in Power BI, Microsoft Fabric, Snowflake, SQL, Python, and R will be instrumental in performing advanced data analysis and visualization to support business decision-making. You will utilize your experience with Azure Data Factory, Databricks, Synapse Analytics, and AWS Glue to develop and maintain data pipelines and queries using SQL and Python. Applying data science techniques such as predictive modeling, classification, clustering, and regression, you will solve business problems and uncover actionable insights. Your hands-on experience in building and deploying machine learning models will be crucial in building, validating, and tuning machine learning models using tools such as scikit-learn, TensorFlow, or similar frameworks. Collaborating with stakeholders, you will translate business questions into data science problems and communicate findings in a clear, actionable manner. You will use statistical techniques and hypothesis testing to validate assumptions and support decision-making. Documenting data science workflows and maintaining the reproducibility of experiments and models will ensure the success of analytics projects. Additionally, you will support the Data Analytics Manager in delivering analytics projects and mentoring junior analysts. Professional certifications such as Microsoft Certified: Power BI Data Analyst Associate (PL-300), SnowPro Core Certification (Snowflake), Microsoft Certified: Azure Data Engineer Associate, and AWS Certified: Data Analytics Specialty are preferred or in progress to enhance your expertise in the field.,

We are looking for a Senior Data Scientist to join our Technology team at Clarivate. You will get the opportunity to work on interesting IP data and interesting challenges to create insights and drive business acumen to add value to our world class products and services About You experience, education, skills, and accomplishments Advanced degree in Computer Science, Statistics, Engineering, Physics, Mathematics, or other quantitative majors, or equivalent work experience. Atleast 4 years of industry experience in the application of ML and NLP Excellent understanding of ML, NLP, and statistical methodologies in a data analytics environment Good programming skills (Python, Java, R or C++) It would be great if you have, Experience with large language model Ability to test ideas and adapt methods quickly end to end from data extraction to implementation and validation Experience with search engines, classification algorithms, recommendation systems, and relevance evaluation methodologies What will you be doing in this role? Researches and identifies Machine Learning (ML) and Natural Language Processing (NLP) methods and algorithms to solve specific problems to improve user experience on IP & Science data and websites Implements these methods and devises appropriate test plans to validate and compare the different approaches Identifies new applications of ML and NLP in the context of Clarivate Analytics extensive sets of content and data Explores existing data for insights and recommends additional sources of data for improvements About the Team You would be part of our incredible data science team of Intellectual property (IP) group & work closely with product and technology teams spreads across various locations worldwide. Hours of Work This is a permanent position with Clarivate.9 hours per day including lunch break. you should be flexible with working hours to align with globally distributed teams and stakeholders.

We are looking for a Senior Data Scientist to join our Technology team at Clarivate. You will get the opportunity to work on interesting IP data and interesting challenges to create insights and drive business acumen to add value to our world class products and services About You experience, education, skills, and accomplishments Advanced degree in Computer Science, Statistics, Engineering, Physics, Mathematics, or other quantitative majors, or equivalent work experience. Atleast 4 years of industry experience in the application of ML and NLP Excellent understanding of ML, NLP, and statistical methodologies in a data analytics environment Good programming skills (Python, Java, R or C++) It would be great if you have, Experience with large language model Ability to test ideas and adapt methods quickly end to end from data extraction to implementation and validation Experience with search engines, classification algorithms, recommendation systems, and relevance evaluation methodologies What will you be doing in this role? Researches and identifies Machine Learning (ML) and Natural Language Processing (NLP) methods and algorithms to solve specific problems to improve user experience on IP & Science data and websites Implements these methods and devises appropriate test plans to validate and compare the different approaches Identifies new applications of ML and NLP in the context of Clarivate Analytics extensive sets of content and data Explores existing data for insights and recommends additional sources of data for improvements About the Team You would be part of our incredible data science team of Intellectual property (IP) group & work closely with product and technology teams spreads across various locations worldwide. Hours of Work This is a permanent position with Clarivate.9 hours per day including lunch break. you should be flexible with working hours to align with globally distributed teams and stakeholders.

We are looking for a Data Scientist to join our Technology team at Clarivate. You will get the opportunity to work on interesting IP data and interesting challenges to create insights and drive business acumen to add value to our world class products and services About You experience, education, skills, and accomplishments Advanced degree in Computer Science, Statistics, Engineering, Physics, Mathematics, or other quantitative majors, or equivalent work experience. Atleast 2 years of industry experience in the application of ML and NLP Excellent understanding of ML, NLP, and statistical methodologies in a data analytics environment Good programming skills (Python, Java, R or C++) It would be great if you have, Experience with large language model Ability to test ideas and adapt methods quickly end to end from data extraction to implementation and validation Experience with search engines, classification algorithms, recommendation systems, and relevance evaluation methodologies What will you be doing in this role? Researches and identifies Machine Learning (ML) and Natural Language Processing (NLP) methods and algorithms to solve specific problems to improve user experience on IP & Science data and websites Implements these methods and devises appropriate test plans to validate and compare the different approaches Identifies new applications of ML and NLP in the context of Clarivate Analytics extensive sets of content and data Explores existing data for insights and recommends additional sources of data for improvements

The Model Validation Senior Specialist role at Deutsche Bank, based in Mumbai, India, falls under the Model Risk Management department. The primary objective is to manage model risk globally by conducting independent model validation, identifying and mitigating model risks, and supporting the overall model risk management framework. This position focuses on validating stress testing models for the CCAR PPNR umbrella within DB USA, necessitating an understanding of various business segments such as Corporate Banking, Private Banking, and Investment Banking. The incumbent will be responsible for tasks including model performance testing, scenario analysis, and developing challenger models. Automation of processes and framework enhancement to drive efficiency is a key aspect of the role. The ideal candidate should have 2-3 years of experience in model development/validation or related areas, with a preference for previous exposure to stress testing (DFAST/CCAR/ICAAP). Knowledge of B/PPNR models across different business lines and familiarity with financial statements analysis will be advantageous. Proficiency in statistical techniques, analytical skills, and experience with software packages like R and Python are essential. Strong communication skills, report drafting abilities, and a background in Mathematics, Statistics, Economics, Engineering, or MBA are preferred. Additionally, holding a CFA/FRM certification or expertise in Business Intelligence tools will be beneficial for the role. Deutsche Bank offers a comprehensive benefits package that includes a competitive leave policy, gender-neutral parental leaves, childcare assistance benefit, sponsorship for industry certifications, and healthcare coverage for employees and dependents. The organization emphasizes training, coaching, and continuous learning to support career progression. The culture at Deutsche Bank promotes responsibility, commercial thinking, initiative, and collaboration, fostering an environment where employees are empowered to excel together every day. For more information about Deutsche Bank and its teams, please visit the company website at https://www.db.com/company/company.htm. The company values diversity and inclusivity, encouraging applications from individuals of all backgrounds to contribute to a positive and fair work environment.,

You are a highly skilled and motivated Senior Quantitative Finance Analyst (Financial Engineer) sought by NuQuants, a division of Zivanta Analytics, specializing in innovative financial analytical solutions for US financial institutions. The role, based in Kolkata, India, involves conducting quantitative analysis, modeling cash flows, assessing market risks, and supporting valuation processes within the US banking sector. Your key responsibilities include performing detailed analysis and modeling of various asset classes, developing quantitative/analytic models, utilizing advanced programming skills in Python, designing improvements to reporting structures, conducting sensitivity analysis, interfacing with clients and engineering teams, working with financial data sets and applications, preparing comprehensive reports, and staying updated with industry trends and best practices. Minimum qualifications entail a Masters/Ph.D. in a quantitative field, proficiency in Python/SQL programming, strong quantitative analysis skills, interest in financial markets, and experience with financial data sets and applications. Preferred qualifications include exposure to the US banking sector, excellent communication skills, attention to detail, analytical mindset, project management skills, self-motivation, and flexibility to work in a collaborative environment with different time zones. The work location is based on a hybrid schedule with 3 days on site and 2.5 days working from home, preferably for candidates in Kolkata. Compensation is commensurate with experience, and 15 days of paid vacation are provided. The job offers an opportunity to contribute to strategic decision-making in the US banking sector, work with innovative technology, and collaborate in a fast-paced environment. If you are interested in this role, please share your updated CV with hr@zivanta-analytics.com. NuQuants looks forward to meeting you and wishes you all the best in your application.,

As part of Goldman Sachs Asset and Wealth Management (AWM), you will have the opportunity to provide asset management, wealth management, and banking expertise to a diverse range of consumers and institutions globally. Collaborating with various teams within the firm, you will play a crucial role in assisting individuals and institutions in navigating changing markets and taking control of their financial lives. The Fixed Income and Liquidity Solutions team, a part of AWM, offers a comprehensive suite of global products tailored to deliver fixed income and money market portfolio solutions. You will work with a wide array of clients, including pension funds, endowments, foundations, financial institutions, insurers, and high net worth individuals. Focusing on investing and advising across various sectors of the fixed income market, from traditional to more specialized products, your contributions will directly impact clients" financial objectives. As a quantitative engineering strategist within Goldman Sachs Asset Management, you will be at the forefront of the business, utilizing analytical methods to solve real-world challenges. Your collaboration with portfolio managers across different asset classes will provide valuable quantitative insights that drive business and investment decisions. Your proficiency in mathematics, programming, and logical thinking will be instrumental in developing quantitative models that contribute to our success. Your responsibilities will involve closely working with portfolio managers to create quantitative models and tools for portfolio management processes, developing sustainable production systems adaptable to a fast-paced environment, and utilizing advanced statistical techniques to enhance portfolio construction and performance. Additionally, you will be tasked with implementing mathematical models in production-quality software and creating rigorous data management tools to support the investment process. To excel in this role, you should possess a background in a quantitative discipline such as mathematics, engineering, physics, or computer science, with a preference for Masters or PhD qualifications. Experience in municipal and corporate credit markets is advantageous, along with strong mathematical and analytical skills. Proficiency in at least one programming language, a proven track record in software development, excellent communication skills, and the ability to innovate solutions to commercial challenges are essential qualities. Joining the Goldman Sachs engineering culture means being part of a team that strives to make things not just happen but also possible. Engage in solving complex engineering problems, connecting people and capital with innovative ideas, and transforming data into actionable insights through cutting-edge software and systems. Embrace the dynamic environment that demands innovative strategic thinking and offers opportunities to push the boundaries of digital possibilities. Goldman Sachs is committed to leveraging the diversity of its workforce to drive growth and success for its clients, shareholders, and communities globally. By fostering a culture of inclusion, providing professional development opportunities, and supporting personal well-being, the firm aims to empower individuals to reach their full potential. Explore the world of finance, innovation, and opportunity with Goldman Sachs, where your unique skills and perspective can make a meaningful impact.,

Bluevine is transforming small business banking with innovative solutions like checking, lending, and credit, all tailored to help entrepreneurs thrive. With best-in-class technology, advanced security, and a deep understanding of the small business community, Bluevine is empowering entrepreneurs to grow with confidence. Backed by leading investors like Lightspeed Venture Partners, Menlo Ventures, 83North, and Citi Ventures, Bluevine has been supporting SMBs since 2013, serving over 750,000 customers nationwide and growing a dynamic global team of 500 people. The mission of Bluevine is to fuel small businesses with the financial tools they need to succeed. At Bluevine, you will be part of a collaborative, fast-paced team that is reshaping the future of banking. Are you ready to make an impact This is a hybrid role at Bluevine. The company prides itself on its collaborative culture, which is believed to be best maintained through in-person interactions and a vibrant office environment. All offices have reopened in accordance with local guidelines and are following a hybrid model. In-office days will be determined by location and discipline. Role Summary: Bluevine is looking for a skilled and motivated Credit Strategy Analyst II to join the Credit and Pricing Strategy team. This role requires a strong analytical mindset with hands-on experience in analysis, strategy development, and real-time automated decisioning. The candidate will be responsible for designing, optimizing, and implementing risk and pricing strategies by leveraging analytics, automated decisioning systems, and statistical models to drive top-line growth and profitability. This position sits at the intersection of strategy, analytics, and engineering, ensuring that strategies are effectively implemented in production through internal decision engines. The ideal candidate should possess business acumen, technical expertise, and a good understanding of risk-based decision-making in a high-growth financial environment. Responsibilities: - Develop and Optimize Strategies: Build, refine, and implement data-driven risk and pricing strategies, balancing credit risk and funding. - Automated Decisioning & Implementation: Define and develop end-to-end automated decision workflows, integrating them into internal digital underwriting engines using Python. - Analytics: Perform in-depth analysis on large datasets to identify patterns, assess risk, and refine pricing strategies, ensuring data-driven decision-making. - Experimentation & Continuous Optimization: Design and execute A/B tests to refine decision-making processes. - Cross-Functional Collaboration: Work closely with Data Engineering, Product, and Data Science to gather insights and conduct analysis of potential strategies. - Monitoring & Feedback Loops: Develop and maintain dashboards to track key performance metrics. What are we looking for - Technical Proficiency: Strong foundation in SQL and Python/R. - Analytical & Problem-Solving Skills: Ability to translate raw data into actionable insights, leveraging statistical techniques and data visualization tools. - Communication: Ability to translate complex analytical concepts into business-friendly insights for stakeholders. - Adaptability & Entrepreneurial Mindset: Thrives in fast-paced, high-growth environments, handling ambiguity with confidence. - Experimentation & Optimization: Experience with A/B testing and iterative improvements in decision-making process. Required Experience and Education: - Bachelor's Degree in a quantitative field (Mathematics, Statistics, Economics, Engineering, Data Science, or related disciplines). - 1-2 years of relevant experience in analytics/strategy. - High proficiency in SQL, Python/R, and Excel. - Knowledge of dashboarding tools like Tableau, Power BI, Metabase, etc. Not required, but a plus: - Familiarity with risk modeling, credit decisioning frameworks, and pricing elasticity analysis. - Experience in financial services, especially U.S. banking, fintech, credit line, or credit card industries. - Exposure to machine learning models and deployment in risk/credit decisioning. Benefits & Perks: - Excellent group health coverage and life insurance. - Stock options. - Hybrid work model. - Meal allowance. - Transportation assistance (terms and conditions apply). - Generous paid time off plan, Holidays. - Company-sponsored mental health benefits. - Financial advisory services for both short- and long-term goals. - Learning and development opportunities to support career growth. - Community-based volunteering opportunities.,

The Smart Cube, a WNS company, is seeking Assistant Managers who will collaborate with the Project Lead to design effective analytical frameworks aligned with client objectives. The Assistant Managers will translate requirements into clear deliverables, manage data preparation, perform quality checks, and ensure analysis readiness. They should possess expertise in implementing analytical techniques and machine learning methods such as regression, decision trees, segmentation, forecasting, and algorithms like Random Forest, SVM, and ANN. Additionally, they are responsible for sanity checks, quality control, and interpreting results in a business context to identify actionable insights. Assistant Managers will independently handle client communications, interact with onsite leads, and manage the entire project lifecycle from initiation to delivery. This includes translating business requirements into technical specifications, overseeing data teams, ensuring data integrity, and facilitating communication between business and technical stakeholders. They will lead process improvements in analytics and act as project leads for cross-functional coordination. In terms of client management, Assistant Managers will serve as client leads, maintain strong relationships, participate in deliverable discussions, and guide project teams on execution strategies. Proficiency in connecting databases with Knime, understanding SQL concepts, and designing Knime ETL workflows to support BI tools is required. They must also be proficient in PowerBI for building dashboards and supporting data-driven decision-making. Knowledge of leading analytics projects using PowerBI, Python, and SQL to generate insights is essential. Ideal candidates should have 4-7 years of experience in advanced analytics across Marketing, CRM, or Pricing in Retail or CPG. Experience in other B2C domains is also acceptable. Proficiency in handling large datasets using Python, R, or SAS, and experience with multiple analytics or machine learning techniques is required. Candidates should have a good understanding of consumer sectors such as Retail, CPG, or Telecom, and experience with various data formats and platforms including flat files, RDBMS, Knime workflows and server, SQL Server, Teradata, Hadoop, and Spark. Strong written and verbal communication skills are essential for creating client-ready deliverables using Excel and PowerPoint. Basic knowledge of statistical and machine learning techniques like regression, clustering, decision trees, forecasting, and other ML models is also necessary. Knowledge of optimization methods, supply chain concepts, VBA, Excel Macros, Tableau, and Qlikview will be an added advantage. Qualifications: - Engineers from top tier institutes (IITs, DCE/NSIT, NITs) or Post Graduates in Maths/Statistics/OR from top Tier Colleges/Universities - MBA from top tier B-schools,

You will be responsible for fetching and transforming data from various systems, conducting in-depth analyses to identify gaps, opportunities, and insights, and providing recommendations that support strategic business decisions. Your key responsibilities will include data extraction and transformation, data analysis and insight generation, visualization and reporting, collaboration with cross-functional teams, and building strong working relationships with external stakeholders. You will report to the VP Business Growth and work closely with clients. To excel in this role, you should have proficiency in SQL for data querying and Python for data manipulation and transformation. Experience with data engineering tools such as Spark and Kafka, as well as orchestration tools like Apache NiFi and Apache Airflow, will be essential for ETL processes and workflow automation. Expertise in data visualization tools such as Tableau and Power BI, along with strong analytical skills including statistical techniques, will be crucial. In addition to technical skills, you should possess soft skills such as flexibility, excellent communication skills, business acumen, and the ability to work independently as well as within a team. Your academic qualifications should include a Bachelors or Masters degree in Applied Mathematics, Management Science, Data Science, Statistics, Econometrics, or Engineering. Extensive experience in Data Lake architecture, building data pipelines using AWS services, proficiency in Python and SQL, and experience in the banking domain will be advantageous. Overall, you should demonstrate high motivation, a good work ethic, maturity, personal initiative, and strong oral and written communication skills to succeed in this role.,

Key Responsibilities: Prepare and analyze ongoing remediation reporting, identifying trends and/or anomalies warranting additional research. Oversee ongoing reporting and deep dive analysis into KPIs and KRIs. Establish mechanisms and technical queries to combine available data, and conduct detailed analysis to identify opportunities for process enhancements, early warning triggers, and health drivers Engage with Issue Management teams to support opportunities for improvements and consistent reporting/monitoring across the teams. Oversee and ensure compliance with model and non-model governance requirements for the full lifecycle of applicable tools. Develop presentations synthesizing analysis for reporting to both internal and regulatory audiences. Lead projects for reporting development and data integration. Provide process focused analytics support to remediation and related process stakeholders. Analyze all aspects of the remediation experience by developing indices using additional variables, including but not limited to, remediation volume, key drivers, and similar. Qualifications/Requirements: Bachelor's degree and a minimum of 8+ years of hands-on reporting and analytics experience OR in lieu of a Bachelor's Degree, a High School Diploma / GED and a minimum of 11+ years of hands-on reporting and analytics experience Minimum 2 years experience in Artificial Intelligence services including transcription, natural language processing, and speech technologies. Minimum 2 years’ experience utilizing statistical techniques, e.g., modeling, A/B testing, and segmentation. 3+ years of experience with proven ability to extract unstructured and structured data with strong programming ability in SAS, SQL, R, Python or other programming language. Desired Characteristics: Bachelor's degree, preferably in a quantitative discipline, such as statistics, mathematics, or engineering. Strong project management, communications, multi-tasking, ability to work independently, relationship management skills are keys to success. Solid understanding of card industry financial P&L drivers and key sensitivities, with business performance reporting experience. Demonstrated ability to manage complexity and multiple initiatives. Ability to perform ad-hoc analysis, glean and form business insights under aggressive timelines. Results-oriented; ready to challenge the status quo for continuous improvement. Eligibility Criteria: You must be 18 years or older You must have a high school diploma or equivalent You must be willing to take a drug test, submit to a background investigation and submit fingerprints as part of the onboarding process You must

Work Timings : 12:30 PM to 9:30 PM Hybrid Work: 3 days' Work from office as of now and may subject to change in future Role Purpose : Manage all the analysts in the Bangalore based team and develop their skills in using various risk management tools and techniques. Assist the department head in maintaining and enhancing productivity of the department. Key Responsibilities : As the second senior-most member of the team, assist the department head in all matters and depute for the department head when required. Develop competencies to assume the department head role at short notice. Design and implement risk management models for consumer lending products. Manage Projects, train and supervise team members in various risk management tools and techniques. Acquire and update knowledge of 1FBSSPLs customer information database and overall business economics. Work on development and deployment of risk management systems and processes. Undertake preparation and upgradation of risk related systems and policies. Preferred candidate profile Key Requirements : Professional with analytics experience preferably in Credit Card Domain . Must have 5 to 6 years hands-on experience in analytical tools like SAS, SQL (advanced) , and advanced excel functions. Experience in R, Python, and BI tools (Tableau, PowerBI, etc.) would be an added advantage. Should have good understanding of statistical concepts specially related to classification, regression, and time-series models. Must have worked on at least one of the following statistical techniques like logistic regression, forecasting, segmentation, etc. Extensive experience in production deployment of MIS reports as well as ad-hoc analysis. Self-driven, ability to work independently, as well as handle a small team. Minimum 8 years of relevant experience. Should have excellent communication skills to interact with senior Bank personnel.

As a Data Science Associate Consultant at ZS, you will design, develop, and execute high-impact analytics solutions for large, complex, structured, and unstructured data sets to help clients make better fact-based decisions. Your responsibilities will include staying updated with the latest developments in Deep Learning and AI research, implementing and fine-tuning advanced models in deep learning, collaborating with cross-functional teams to develop and deploy machine learning models in production, contributing to research projects advancing AI and machine learning, and integrating engineering principles into data science workflows. You will be expected to have a Bachelor's or master's degree or PhD in Computer Science (or Statistics) from a premier institute, along with 4-7 years of Data Science experience. Proficiency in generative AI, deep learning, statistical techniques, and programming languages such as Java/Python/R is required. Additionally, you should have knowledge of big data/advanced analytics concepts and algorithms, excellent oral and written communication skills, strong attention to detail, critical thinking, problem-solving skills, motivation, work ethic, and maturity. Exposure to Generative AI is a plus. ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth, and professional development. The company is committed to providing employees with a flexible and connected way of working, allowing a combination of work from home and on-site presence at clients/ZS offices. Travel may be required based on the business needs of your project and client, providing opportunities for professional growth and diverse experiences. ZS is focused on building a diverse and inclusive company where individuals from all backgrounds can bring their passions to inspire life-changing impact. The company encourages candidates to apply even if they do not meet all the requirements listed. ZS is an equal opportunity employer committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law. Candidates interested in applying must possess or be able to obtain work authorization for their intended country of employment. An online application, including a full set of transcripts, is required to be considered. More information can be found at www.zs.com.,

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.

The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Role and responsibilities: Understand business problem and requirements by building domain knowledge and translate to data science problem. Conceptualize and design cutting edge data science solution to solve the data science problem, apply design-thinking concepts. Identify the right algorithms, tech stack, sample outputs required to efficiently adder the end need. Prototype and experiment the solution to successfully demonstrate the value. Independently or with support from team, execute the conceptualized solution as per plan by following project management guidelines. Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization. Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development, and practice development initiatives. Technical and Functional Skills: Bachelors degree in Computer Science with 4 to 6 years of work experience. Must have experience in Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, Python, decision tree, random forest, SAS, clustering classification. Ability to engage clients to understand business requirements and convert the same into technical/modelling problems for solution development. Demonstrate strong interpersonal skills and a comfort interacting with clients from the C-suite to marketing managers to technical specialists. Demonstrated knowledge of analytical/statistical techniques and their applications; a working knowledge of/experience in R and Python is a plus. Demonstrated excellent communications skills, both written and spoken, as well as being able to explain complex technical concepts in plain English. Ability to present results of statistical models in business language. Domain understanding of at least one preferably two verticals amongst Retail, Cable, Technology (not mandate). Knowledge of data visualization tools (Tableau, QlikView, etc.) is a plus. Demonstrate strong analytical and storytelling skills and the ability to find relevant stories from piles of reports. Ability to manage specific tasks to completion with minimal direction. Ideal candidate has been in a consulting role previously. Hands-on expertise on the applied statistical techniques including multi-variate regression, logistic regression, market-mix models, clustering, classification, survival, churn models, speech analytics, image analytics, etc. Ability to collaborate with onsite colleagues in the US & UK. Expert in handling large data, cleansing & preparation for modelling. Very high attention to detail and quality.