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data scientist

CHANEL

<div>
 
 At Chanel, we are focused on creating an inclusive culture that nurtures personal growth, contributing to collective progress. We believe the uniqueness of each individual increases the diversity, complementarity, and effectiveness of our teams. We strongly encourage your application, as we value the perspective, experience and potential you could bring to CHANEL.
 
 
 
 
 About the role:
 
 
 
 CHANEL is now hiring a Data Scientist for our Digital Client Experience (DCX) Data team in New York City. Our ideal Data Scientist is able and experienced to lead advanced analytics and data-driven initiatives that enhance our client experiences digitally and in boutiques. This role will define and execute the data science roadmap, develop machine learning models, and establish best practices&mdash;while operating as a stand-alone contributor within the DCX Data Team.
 
 
 Beyond technical delivery, this role will play a pivotal part in making CHANEL US more AI-driven, piloting Generative AI projects, and driving adoption of advanced analytics across teams through effective change management.
 
 
 
 Required tech:
 
 Python, R, Machine Learning, Big Query, SQL, etc.
 
 
 
 What impact you can create at CHANEL:
 
 
 
 
 <ul>
 <li>
 Own and execute the data science roadmap for CHANEL US, aligned with digital transformation priorities.
 </li>
 <li>
 Design and implement advanced analytics solutions, including predictive modeling, machine learning, and AI-driven use cases.
 </li>
 <li>
 Lead AI adoption initiatives, introducing innovative approaches and piloting Generative AI projects for business impact while protecting the brand.
 </li>
 <li>
 Drive change management to embed advanced analytics into day-to-day workflows, helping teams embrace technology and new ways of working.
 </li>
 <li>
 Establish data science best practices and frameworks for scalable, production-ready models.
 </li>
 <li>
 Execute end-to-end projects: data preparation, feature engineering, model development, deployment, and monitoring.
 </li>
 <li>
 Implement ML Ops practices for model lifecycle management and scalability.
 </li>
 <li>
 Develop data pipelines and automation workflows, including API integrations for system connectivity.
 </li>
 <li>
 Collaborate cross-functionally with Business teams, legal, Tech, and external partners to integrate solutions into production workflows.
 </li>
 <li>
 Manage stakeholders effectively, ensuring alignment and buy-in across Fragrance &amp; Beauty, Fashion, Watches &amp; Fine Jewelry (WFJ) divisions.
 </li>
 <li>
 Communicate complex concepts simply, delivering clear narratives and actionable recommendations to senior leadership.
 </li>
 <li>
 Promote data storytelling and experimentation (e.g., A/B testing) to validate impact and foster a culture of innovation.
 
 
 
 </li>
 </ul>
 
 You are energized by:
 
 
 
 
 <ul>
 <li>
 Exceptional critical and creative thinking skills including evaluating risks and contingencies, developing structure in ambiguity
 </li>
 <li>
 Data-driven decision making for products and services
 </li>
 <li>
 Excellent project management and communication skills
 </li>
 <li>
 Connecting the dots on pain points, bring a key eye for details and expert problem perception with solutions mindset
 </li>
 <li>
 Ability to translate technical jargon into simple business terms
 </li>
 <li>
 Working in a highly collaborative environment
 </li>
 <li>
 Building strong partnerships across business and technology teams in a global organization
 </li>
 <li>
 Championing change and fostering a culture of accountability and innovation
 
 
 
 </li>
 </ul>
 
 What you will bring to the team:
 
 
 
 
 <ul>
 <li>
 Experience with personalization, recommendation of engines, and segmentation
 </li>
 <li>
 API integration and automation skills (e.g., building pipelines, connecting systems) are a strong plus
 </li>
 <li>
 Familiarity with Salesforce CRM systems and digital transformation programs
 </li>
 <li>
 Luxury retail or client-centric industries favorable but not required
 
 
 
 </li>
 </ul>
 
 Required Skills &amp; Qualifications
 
 
 
 
 <ul>
 <li>
 Minimum of 7 years of experience in data science roles with proven ability to deliver projects independently
 </li>
 <li>
 Expert-level coding skills in Python or R, with strong experience in developing and deploying machine learning models
 </li>
 <li>
 SQL proficiency is mandatory for data manipulation and querying large datasets
 </li>
 <li>
 Hands-on experience with Google Big Query as a core analytics platform
 </li>
 <li>
 Familiarity with Generative AI frameworks and emerging AI technologies
 </li>
 <li>
 Experience with MLOps tools and version control (e.g., Git)
 </li>
 <li>
 Strong business acumen and ability to influence organizational change
 </li>
 <li>
 Exceptional communication and stakeholder management skills, including the ability to simplify complexity for senior leaders
 
 
 
 </li>
 </ul>
 
 Position Logistics:
 
 
 
 
 <ul>
 <li>
 Hybrid work &ndash; required 3 days onsite at CHANEL offices in New York City
 </li>
 <li>
 Minimum of 7 years of experience in data science roles with proven ability to deliver projects independently
 </li>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Data Science or equivalent
 </li>
 <li>
 Chanel, Inc. reserves the right to edit, change, or make exceptions on designations where circumstances where deemed appropriate.
 
 
 
 </li>
 </ul>
 
 
 
 Compensation:
 
 
 
 
 <ul>
 <li>
 The anticipated base salary range for this position is $87,500-$190,000. A base salary is one component of the total compensation for this position. Other forms of variable pay [may/will] be offered for this position. Other components [may/will] include bonus potential, benefits, and/or perks.
 
 
 
 </li>
 </ul>
 
 Benefits and Perks:
 
 
 
 
 <ul>
 <li>
 Wellbeing resources include dedicated paid time off for wellbeing (2-week August Office Closure) and a Wellbeing fund
 </li>
 <li>
 Family and care giving benefits (inclusive of parental leave, fertility support, MilkStork, and Care.com Membership)
 </li>
 <li>
 Generous paid time off policies to include vacation, holiday, sick and volunteer days
 </li>
 <li>
 401K and other incentives
 </li>
 <li>
 Robust healthcare offerings; medical, dental, vision, MDLIVE (virtual care), One Medical, Flexible Spending Accounts (Health Care &amp; Dependent Care), Health Savings Account and Employee Assistance Program
 </li>
 <li>
 Life insurance, Accidental Death &amp; Dismemberment, Short Term Disability, Long Term Disability, Health Advocate, International Business Travel Accident &amp; Medical, and Commuter Transit &amp; Parking
 
 
 
 </li>
 </ul>
 
 Additional Information:
 
 
 
 Chanel is a private company whose values are grounded in creating conditions for people to perform at their best and feel fulfilled and confident in their work. We offer a unique work environment where individuals are encouraged to better understand the brand, the business, and motivations, so that together we can unlock the possibilities of growth. This is reflected in:
 
 
 
 Diversity and Inclusion:
 
 
 
 
 <ul>
 <li>
 At CHANEL, we are intentional in promoting Diversity &amp; Inclusion. We foster respect, empathy, and dignity for all. We believe strongly that the diversity of our people across the full spectrum of human differences is essential to our organisation and the connections we have with each other and our clients.
 </li>
 <li>
 We offer Employee Resource Groups in the US that are voluntary, open to all, employee-led groups formed around a shared identity or lived experience, whose aim is to foster a diverse, inclusive, and equitable community aligned with the values and missions of the communities they support.
 
 
 
 </li>
 </ul>
 
 Chanel Community:
 
 
 
 
 <ul>
 <li>
 CHANEL Community empowers our employees to channel their passions, talents and sense of purpose to contribute to and learn from our communities.
 </li>
 <li>
 Employees are encouraged to take time off annually to volunteer through CHANEL Community. CHANEL also matches employee donations to select charitable organizations.
 
 
 
 </li>
 </ul>
 
 Sustainability:
 
 
 
 
 <ul>
 <li>
 CHANEL Mission 1.5&deg; is our climate action plan. It is focused on transforming the business in line with the ambitions of the Paris Agreement on climate change to limit the average global mean temperature increase to 1.5 degrees Celsius above preindustrial levels.
 </li>
 <li>
 Employees are encouraged to contribute to our US Sustainability efforts at the corporate level and within the divisions, through organized taskforces and initiatives.
 
 
 
 </li>
 </ul>
 
 Arts and Culture:
 
 
 
 
 <ul>
 <li>
 We are committed to extending our legacy of cultural engagement. Global support includes the CHANEL Culture Fund, which supports a select group of leading art culture institutions across the globe, and the CHANEL Next Prize for the next generation of creative talent. US support currently includes Annual sponsorship of the MoMA film program, Tribeca Film Festival programs and Through Her Lens, Support of the Academy Gold Fellowship for Women and Sponsorship of the BAAND Together Dance Festival at Lincoln Center.
 
 
 
 </li>
 </ul>
 
 Fondation Chanel:
 
 
 
 
 <ul>
 <li>
 Since 2011, Fondation CHANEL&rsquo;s mission is for women and girls to be free to shape their own destiny.  Through multi-year partnerships with financial and technical support, Fondation CHANEL is committed to improving the safety and autonomy of women and adolescent girls around the world, impacting over a million women and girls in its first 10 years.
 </li>
 <li>
 For more information, please navigate to the Fondation Chanel website here
 
 
 
 </li>
 </ul>
 
 Career and Leadership Development:
 
 
 
 
 <ul>
 <li>
 We have dedicated in-house teams focused on supporting the onboarding of employees, developing leadership skills via custom programs like Imagine Chanel People, Heart of Leadership and group and individual coaching, and blended online and live classes offered on our Bloom platform and by skilled trainers, such as Shape Your Career, to develop career building skills.
 </li>
 <li>
 Chanel, Inc. benefits and perks are dependent on eligibility and subject to modification by Chanel at any time.
 
 </li>
 </ul>
</div>

Data Scientist

ALICE + OLIVIA

<div>
 
 Location: New York, NY or Secaucus, NJ (Hybrid)
 
 
 Decision Science Engineer (Applied Data Scientist)
 
 
 
 
 
 
 POSITION SUMMARY:
 
 
 
 ALICE + OLIVIA is hiring a Decision Science Engineer to build, operationalize, and own predictive models that improve decision making across Planning, Merchandising/Buying, Customer 360, and Inventory Management. Working primarily within Palantir Foundry as the core analytics and deployment platform, this role bridges data science and platform engineering, translating real-world commercial constraints including seasonality, product lifecycle, allocations, replenishment, promotions/markdowns, and customer behavior into practical, production-grade, human-in-the-loop models.
 
 
 
 
 
 This is a highly cross-functional role with direct, ongoing exposure to business stakeholders and end users, from planners and buyers who consume and act on model outputs, to the teams working within Foundry Workshop applications day-to-day. Understanding how outputs are used in real workflows, and staying close to the people using them, is central to how this role operates. Sitting within the IT organization and serving the full business including DTC, wholesale, planning, and supply chain, this position carries direct visibility to executive business stakeholders. This role is focused on applied data science, decision-support modeling, and model operationalization, not reporting or core data engineering, while partnering closely with Engineering, BI, and the broader Enterprise Applications team.
 
 
 
 
 
 
 RESPONSIBILITIES:
 
 
 <ul>
 <li>
 Design, build, and maintain predictive and statistical models supporting retail planning, buying, inventory, and demand forecasting.
 </li>
 <li>
 Operationalize models within Palantir Foundry using Code Workbook and Code Repository, working against Snowflake as the primary data source and ensuring outputs are production-grade and maintainable.
 </li>
 <li>
 Own and evolve analytics logic and assumptions embedded in planning and buying workflows.
 </li>
 <li>
 Partner with Planning, Buying, Merchandising, and DTC teams to translate business needs into model-driven insights, maintaining direct, ongoing relationships with the stakeholders and end users consuming model outputs.
 </li>
 <li>
 Collaborate with the Enterprise Applications team on Workshop app development to ensure model outputs are surfaced effectively in business-facing Foundry applications.
 </li>
 <li>
 Build models for customer segmentation, CLV, retention/churn, propensity, and campaign targeting (Customer 360).
 </li>
 <li>
 Collaborate with Engineering, who owns data pipelines and Snowflake ingestion, to ensure model inputs are reliable, well-governed, and fit for purpose without owning the underlying data infrastructure.
 </li>
 <li>
 Support human-in-the-loop workflows where planners and buyers can interrogate, override, or adjust model outputs in real time.
 </li>
 <li>
 Validate model outputs against business reality and historical performance, closing the loop directly with end users on model accuracy and relevance.
 </li>
 <li>
 Document methodologies and assumptions to support long-term ownership and institutional knowledge.
 </li>
 </ul>
 
 
 
 
 
 QUALIFICATIONS:
 
 
 <ul>
 <li>
 4 to 8+ years of experience in data science, applied analytics, or predictive modeling.
 </li>
 <li>
 Strong experience building predictive or statistical models including forecasting, optimization, regression, and classification.
 </li>
 <li>
 Proficiency in Python for data analysis, modeling, and production-grade code.
 </li>
 <li>
 Strong SQL and hands-on experience with Snowflake or equivalent cloud data warehouse.
 </li>
 <li>
 Experience with Palantir Foundry strongly preferred, including familiarity with the Foundry Ontology layer, analytics and modeling tooling (Code Workbook, Code Repository), and how model outputs are surfaced through business-facing applications. Candidates who can reason within and contribute to an existing Ontology, and who understand how the semantic data layer connects to model design, will be prioritized.
 </li>
 <li>
 Familiarity with experiment design and causal inference.
 </li>
 <li>
 Experience with time-series forecasting at scale.
 </li>
 <li>
 Retail domain experience strongly preferred, including familiarity with demand vs net sales, sell-through, markdowns, planning vs buying workflows, seasons, price groups, and store vs e-commerce dynamics.
 </li>
 <li>
 Experience working with messy, real-world data and designing models that support business judgment.
 </li>
 <li>
 Ability to reason about semantic or ontology-based data models.
 </li>
 <li>
 Strong communication and relationship skills, comfortable working directly with planners, buyers, and business stakeholders, and able to translate model outputs into decisions, not just insights.
 </li>
 <li>
 Long-term ownership mindset for maintaining and evolving models over time.
 </li>
 <li>
 Hands-on experience building or contributing to Palantir Foundry Workshop applications.
 </li>
 <li>
 Background in wholesale or multi-channel retail, including familiarity with the operational differences between DTC, wholesale, and brick-and-mortar planning cycles.
 </li>
 <li>
 Exposure to agent-based or AI-assisted analytics workflows.
 </li>
 <li>
 Experience working within a formal data governance or steerco-driven prioritization structure.
 </li>
 <li>
 Familiarity with Snowflake-native development patterns including dbt, Snowpark, or similar.
 </li>
 </ul>
 
 
 
 
 
 ADDITIONAL INFORMATION:
 
 
 
 This role sits within the IT organization, reporting to the VP of Information Technology, and operates across the full business including Planning, Merchandising/Buying, DTC, and Supply Chain. Engineering owns ETL, data pipelines, and Snowflake ingestion. BI owns reporting and dashboards. This role owns predictive modeling, decision-support analytics, and model operationalization within Palantir Foundry. Work is prioritized through a cross-functional steering committee with direct business stakeholder representation, ensuring this role has structured visibility into commercial priorities and executive-level exposure from day one.
 
 
 
 
 
 ALICE + OLIVIA is at an inflection point in how it uses data to make decisions. This role is central to that transformation, building the analytics capability that connects our Palantir Foundry investment to real commercial outcomes across every part of the business. This is not a role that maintains existing infrastructure or produces reports. It is a greenfield opportunity to own a strategic function, work directly with the teams making decisions, and build something that compounds in value over time. For the right person, it is a rare combination of technical depth, business proximity, and organizational support.
 
 
 
 
 
 $150,000 -175,000 base salary (This range represents the low and high end of the anticipated base salary range for this NY OR NJ - based position. The base salary will depend on numerous factors such as: experience and qualifications for the role, experience level, skillset, and balancing internal equity relative to other A+O employees.)
 
</div>

Andiamo

<div>
 
 About The Role
 
 
 
 When you work in this role, you&rsquo;ll tackle tough problems alongside other scientists and engineers&mdash;people who will challenge your ideas, share knowledge, and collaborate on impactful projects. You&rsquo;ll be doing work that matters, developing solutions to complex real-world problems using data, invention, and rigorous inquiry.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Independently research and develop hypotheses based on diverse real-world datasets.
 </li>
 <li>
 Conduct literature reviews to apply cutting-edge methodologies for extracting meaningful signals from data.
 </li>
 <li>
 Partner with engineers and stakeholders to rigorously explore and test your theories.
 </li>
 <li>
 Stay engaged in the academic community by joining reading circles and attending seminars to keep up with the latest research.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 1&ndash;5+ years of experience in applied data analysis and prediction, preferably in an industry setting.
 </li>
 <li>
 Degree in a technical or quantitative discipline such as statistics, mathematics, physics, electrical engineering, or computer science.
 </li>
 <li>
 Proficiency in Python and SQL.
 </li>
 <li>
 Experience conducting in-depth research projects involving real-world data.
 </li>
 <li>
 Ability to think independently, approach analysis creatively, and communicate complex ideas clearly.
 </li>
 <li>
 Background in finance is not required&mdash;strong research skills are most important.
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Core Benefits: Fully paid medical and dental insurance premiums for employees and dependents, competitive 401k match, employer-paid life and disability insurance.
 </li>
 <li>
 Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms.
 </li>
 <li>
 Learning: Tuition reimbursement, conference and training sponsorship.
 </li>
 <li>
 Time Off: Generous vacation and unlimited sick days, competitive paid caregiver leaves.
 </li>
 <li>
 Hybrid Work Policy: Flexible in-office days with budget for home office setup.
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 The base pay for this role will be between
 
 $165,000 and $300,000
 
 . This role may also be eligible for additional forms of compensation and benefits such as discretionary bonuses, health and wellness plans, and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation will depend on skills, qualifications, and experience.
 
 
 
 About Andiamo
 
 
 
 Talent Partners for the AI Revolution. As a globally recognized staffing and consulting firm, we specialize in placing the top 2% of technology and go-to-market professionals with the world&rsquo;s largest and most well-known companies.
 
 
 For over 20 years, we've maintained the status of tier-one vendor for firms such as Palantir, Amazon, Fluidstack, Bloomberg, Relativity Space, Firefly, MasterCard, Visa, Two Sigma, Citadel, as well as other major financial services firms, elite hedge funds, Google-backed tech start-ups, and major software firms.
 
 
 Our talent solutions include Permanent Placement, Contract Staffing, Executive Search, and Dedicated Recruiting Services (RPO). Find out more at www.andiamogo.com
</div>

MatchPoint

<div>
 
 MatchPoint Solutions is a fast-growing, young, energetic global IT-Engineering services company with clients across the US. We provide technology solutions to various clients like
 
 Uber, Robinhood, Netflix, Airbnb, Google, Sephora, and more!
 
 More recently, we have expanded to working internationally in
 
 Canada, China, Ireland, UK, Brazil, and India
 
 . Through our culture of innovation, we inspire, build, and deliver business results, from ideas to outcome. We keep our clients on the cutting edge of the latest technologies and provide solutions by using industry-specific best practices and expertise.
 
 
 
 
 
 We are excited to be continuously expanding our team. If you are interested in this position, please send over your updated resume. We look forward to hearing from you!
 
 
 
 
 
 
 Job Title: Data Scientist -Growth Analytics
 
 
 
 
 Location: New York City, NY (Hybrid-3 days a week)
 
 
 
 
 Employment Type: Fulltime
 
 
 
 
 
 
 
 
 
 
 
 Responsibilities Growth Strategy &amp; Acquisition
 
 
 <ul>
 <li>
 
 Pricing &amp; Incentive Strategy:
 
 Design and test dynamic pricing models and incentive structures (e.g., first-order discounts, owner bonuses). You will mathematically determine how to stoke demand and aid conversion without eroding our contribution profit margins, ensuring every dollar of "discount" generates long-term ROI.
 </li>
 <li>
 
 The Growth Equation:
 
 Model our acquisition channels (Organic, Paid, Referral, Ambassadors). You will identify which channels have the highest LTV/CAC ratio and tell us where to double down.
 </li>
 <li>
 
 Viral Loops:
 
 Analyze our referral and sharing behaviors. You will calculate our K-factor (virality) and identify product changes to keep our users as our best marketing channel.
 </li>
 </ul>
 
 
 
 
 
 Marketplace Liquidity &amp; Retention
 
 
 <ul>
 <li>
 
 Supply-Led Growth:
 
 Analyze how inventory levels drive organic growth. Does adding 100 power owners in Chicago unlock 1,000 new customers? You will tell us where to focus supply acquisition.
 </li>
 <li>
 
 The "Magic Moments":
 
 Identify the specific user behaviors that lead to long-term retention (e.g., "Users who rent within 7 days of signup retain at 3x").
 </li>
 <li>
 
 Churn Prediction:
 
 Build models to identify at-risk users before they leave, allowing our CX team to intervene.
 </li>
 </ul>
 
 
 
 
 
 Product Conversion (CRO)
 
 
 <ul>
 <li>
 
 Funnel Optimization:
 
 Own the granular analysis of our demand and supply funnels. You will find the leaks in the bucket and design A/B tests to plug them.
 </li>
 <li>
 
 Experimentation:
 
 Help the product team design valid experiments. You ensure we aren't just shipping features, but moving metrics with statistical significance.
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 
 The "Grinder" Mentality:
 
 You are relentlessly curious. You are the type of person who can't put something down until you figure out the why.
 </li>
 <li>
 
 Growth Native:
 
 You speak the language of growth: CAC, LTV, ROAS, K-Factor, Churn, and Cohorts. You understand that "Data Science" is a tool to make money and grow the user base.
 </li>
 <li>
 
 Product Fluency:
 
 You understand product growth loops and can quickly execute and extract insights from demand funnels and A/B tests
 </li>
 <li>
 
 5+ Years Experience:
 
 Ideally in a Consumer Marketplace or high-growth B2C app. You have seen how a company scales and understand the data infrastructure needed to support it.
 </li>
 <li>
 
 Note:
 
 We are open to less experience if you have exceptional raw talent and a portfolio of solving complex growth problems.
 </li>
 <li>
 
 Technical Fluency:
 
 Expert-level SQL. Proficient in Python/R for modeling. Experience with growth stacks (PostHog, Mixpanel, AppsFlyer, Segment) and visualization tools.
 </li>
 </ul>
 
 
 
 
 
 
 
 MatchPoint Solutions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
 
 
 
 
 
 This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
 
</div>

Data Scientist with Growth Analytics

<div>
 Senior Data Scientist
 
 
 
 About The Role
 
 
 
 Partner with product and engineering to turn data into decisions. You&rsquo;ll design experiments, build predictive models, and deliver insights that move key metrics.
 
 
 What You&rsquo;ll Do
 
 
 <ul>
 <li>
 Frame problems, define success metrics, and design A/B tests or quasi-experiments.
 </li>
 <li>
 Build models for prediction, ranking, segmentation, or forecasting.
 </li>
 <li>
 Develop data pipelines and features with engineering partners.
 </li>
 <li>
 Communicate results clearly to technical and non-technical audiences.
 </li>
 <li>
 Establish best practices for measurement, causal inference, and model monitoring.
 
 
 </li>
 </ul>
 What We&rsquo;re Looking For
 
 
 <ul>
 <li>
 6+ years in applied data science or analytics.
 </li>
 <li>
 Proficiency in Python, SQL, and ML libraries (pandas, scikit-learn, PyTorch/TensorFlow).
 </li>
 <li>
 Experience with experimentation, causal methods, or time-series.
 </li>
 <li>
 Strong stakeholder management and storytelling with data.
 
 
 </li>
 </ul>
 
 About Andiamo
 
 
 
 Talent Partners for the AI Revolution. As a globally recognized staffing and consulting firm, we specialize in placing the top 2% of technology and go-to-market professionals with the world&rsquo;s largest and most well-known companies.
 
 
 For over 20 years, we've maintained the status of tier-one vendor for firms such as Palantir, Amazon, Fluidstack, Bloomberg, Relativity Space, Firefly, MasterCard, Visa, Two Sigma, Citadel, as well as other major financial services firms, elite hedge funds, Google-backed tech start-ups, and major software firms.
 
 
 Our talent solutions include Permanent Placement, Contract Staffing, Executive Search, and Dedicated Recruiting Services (RPO). Find out more at www.andiamogo.com
</div>

Senior Data Scientist - Medical Software Company

Deutsche Bank

<div>
 
 
 
 Job Description:
 
 
 
 
 
 Job Title:
 
 AFC Modelling &ndash; Data Scientist
 
 
 
 Corporate Title:
 
 Associate - Vice President
 
 
 
 Location:
 
 New York, NY
 
 
 
 
 
 
 Overview
 
 
 
 
 Group Strategic Analytics , GSA concentrates Deutsche Bank&rsquo;s quantitative and modelling expertise within a single unit. With group-wide responsibility for model development, GSA takes a cross-business and cross-functional approach to solving quantitative modelling, analytics scenarios, and rolls out common development standards.
 
 
 
 
 
 
 
 Modelling supports the Anti Financial Crime (AFC) function, which performs a crucial role in keeping Deutsche Bank&rsquo;s business operations and global financial services clean from financial crime while serving the interests of the Bank and society. Our regional/global matrix structure allows for flexible responses to challenges in the core areas of: Anti-Money Laundering, Sanctions &amp; Embargoes, Anti-Fraud, Bribery &amp; Corruption, Investigations &amp; Intelligence, Monitoring &amp; Screening, and Risk Assessment.
 
 
 
 
 
 
 
 Our team will provide you with opportunities to learn, grow and define your career. We foster an open, diverse, and inclusive team culture, that is engaged and well-supported for prosperity and enjoyment of a life/work balance.
 
 
 
 
 
 
 
 What We Offer You
 
 
 <ul>
 <li>
 A diverse and inclusive environment that embraces change, innovation, and collaboration
 </li>
 <li>
 A hybrid working model, allowing for in-office / work from home flexibility, generous vacation, personal and volunteer days
 </li>
 <li>
 Employee Resource Groups support an inclusive workplace for everyone and promote community engagement
 </li>
 <li>
 Competitive compensation packages including health and wellbeing benefits, retirement savings plans, parental leave, and family building benefits
 </li>
 <li>
 Educational resources, matching gift and volunteer programs
 </li>
 </ul>
 
 
 
 
 
 What You&rsquo;ll Do
 
 
 <ul>
 <li>
 Drive model implementation (from prototype to production), following rigorous coding, testing, and documentation best practice
 </li>
 <li>
 Responsible for Driving and execution of the Anti-Money Laundering (AML) Transaction Monitoring Americas data strategy in line with the Global Data Strategy/Framework
 </li>
 <li>
 Develop and evolve platform reporting statistics/data to monitor ongoing model success; perform 'deep dives' to interpret data quality issues, identify remediation and track to resolution
 </li>
 <li>
 Represent the group in various data governance forums, and clearly communicate data related issues and potential resolution paths
 </li>
 <li>
 Work with Business (1LOD) to understand the products being offered and define specifications/red flags for Transaction Monitoring models
 </li>
 <li>
 Review and address open AML TM findings in a timely fashion, work in partnership with AFC stakeholders to develop and drive initiatives that transform and modernize the capabilities and services of Monitoring within the AFC function
 </li>
 </ul>
 
 
 
 
 
 How You&rsquo;ll Lead
 
 
 <ul>
 <li>
 Establish a clear vision and goals for the team, Inspire the team to perform well and achieve business goals; provide guidance and instruction to the team, and coach them as needed.
 </li>
 <li>
 Oversee daily activities and progress towards goals, and ensure the team is adequately equipped to perform their duties.
 </li>
 <li>
 Prioritize tasks and allocating tasks to the team accordingly. The role will be collaborating across multiple teams within the M&amp;S (Monitoring &amp; Screening) function.
 </li>
 </ul>
 
 
 
 
 
 Skills You&rsquo;ll Need
 
 
 <ul>
 <li>
 Bachelor&rsquo;s/Master&rsquo;s degree in Computer Science, Data Science, Management Information System (MIS), Information Management, or equivalent
 </li>
 <li>
 Previous relevant experience conducting data science or Model Development in a business setting coupled with excellent programming skills, predominantly across the Python/Anaconda suite (Scikit-learn, Pandas, Numpy)
 </li>
 <li>
 Experience in Financial Crimes space with expertise in AML Transaction Monitoring and Advisory, with a deep understanding of transaction monitoring data for various lines of businesses, AML red flags, and AML typologies.
 </li>
 <li>
 Proficient in Financial Crime Compliance covering multiple product lines, such as Correspondent Banking, Private Banking, Wealth Management, Brokerage, Trade, and Asset Management.
 </li>
 <li>
 Demonstrated experience in Relational databases, Structured Query Language (SQL), Big Data Hadoop, Hive Query Language (HQL), Data visualization tools.
 </li>
 </ul>
 
 
 
 
 
 Skills That Will Help You Excel
 
 
 <ul>
 <li>
 Flexible and able to adapt to urgent deliverable timelines
 </li>
 <li>
 A positive outlook in a goal-oriented organization
 </li>
 <li>
 Able to demonstrate excellent analytical, judgment, and research skills
 </li>
 <li>
 Meticulous with a strong attention to detail and the ability to multitask
 </li>
 <li>
 Able to interpret complex requirements and work proactively with stakeholders in different organizational units
 </li>
 </ul>
 
 
 
 
 
 Expectations
 
 
 
 
 
 
 It is the Bank&rsquo;s expectation that employees hired into this role will work in the New York City office in accordance with the Bank&rsquo;s hybrid working model.
 
 
 
 
 
 Deutsche Bank provides reasonable accommodations to candidates and employees with a substantiated need based on disability and/or religion.
 
 
 
 
 
 The salary range for this position in New York City is $110,000 to 252,500. Actual salaries may be based on a number of factors including, but not limited to, a candidate&rsquo;s skill set, experience, education, work location and other qualifications. Posted salary ranges do not include incentive compensation or any other type of remuneration.
 
</div>

AFC Modelling - Data Scientist - Associate - Vice President

Two Sigma

<div>
 Position Summary
 
 
 Two Sigma is a leading quantitative investment management and trading firm. The company applies a scientific approach to investing, combining cutting-edge technology, artificial intelligence, data science, and quantitative research with rigorous human inquiry to capitalize on market opportunities and deliver alpha for investors.
 
 
 Our team of engineers, quantitative researchers and data scientists looks beyond the traditional to test hypotheses and develop creative solutions to some of the world&rsquo;s most complex economic problems.
 
 
 When you work with us, you tackle tough problems alongside other scientists and engineers. People who will challenge your ideas. Who you can really learn from, and collaborate with. And you&rsquo;ll be doing work that matters to a lot of people, too. Our investors include some of the world&rsquo;s largest retirement funds, research institutions, educational endowments, healthcare systems and foundations. We admire what they do, and we&rsquo;re proud to serve these organizations.
 
 
 
 You Will Take On The Following Responsibilities
 
 
 
 <ul>
 <li>
 Independently research and develop hypotheses based on diverse and unique real-world datasets.
 </li>
 <li>
 Conduct literature reviews to develop and apply cutting-edge methodologies for extracting meaningful signals from our vast data holdings.
 </li>
 <li>
 Partner with our engineers and business stakeholders to rigorously explore and test your theories.
 </li>
 <li>
 All the while, you&rsquo;ll remain engaged in the academic community. As examples, you can:
 </li>
 <li>
 Join our reading circles to stay up to date on the latest research papers in your fields
 </li>
 <li>
 Attend academic seminars to learn from thought leaders from top universities
 
 
 </li>
 </ul>
 
 You Should Possess The Following Qualifications
 
 
 
 <ul>
 <li>
 Degree in a technical or quantitative discipline, like chemistry, computer science, economics, statistics, or quantitative social science with an applied empirical focus (all levels welcome, from bachelor&rsquo;s to doctorate)
 </li>
 <li>
 Proficient in Python and SQL
 </li>
 <li>
 Performed an in-depth research project, examining real-world data
 </li>
 <li>
 Are an independent thinker who can creatively approach data analysis and communicate complex ideas clearly
 </li>
 <li>
 You don&rsquo;t need a background in finance. It&rsquo;s nice to have, but more than half of Two Sigma&rsquo;s employees come from outside the finance industry. If you&rsquo;ve got the research skills, we can teach you the financial aspects of the job.
 </li>
 <li>
 We are particularly enthusiastic about people who bring a quantitative and data-driven mindset to nontraditional and difficult-to-quantify problems.
 
 
 </li>
 </ul>
 
 You Will Enjoy The Following Benefits
 
 
 
 <ul>
 <li>
 Core Benefits: Fully paid medical and dental insurance premiums for employees and dependents, competitive 401k match, employer-paid life &amp; disability insurance
 </li>
 <li>
 Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms
 </li>
 <li>
 Learning: Tuition reimbursement, conference and training sponsorship
 </li>
 <li>
 Time Off: Generous vacation and unlimited sick days, competitive paid caregiver leaves
 </li>
 <li>
 Hybrid Work Policy: Flexible in-office days with budget for home office setup
 
 
 </li>
 </ul>
 The base pay for this role will be between $165,000 (Bachelors), $170,000 (Masters), and $190,000 (PhD) based on academic degree conferred. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.
 
 
 We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.
 
 
 Two Sigma is committed to providing reasonable accommodations to qualified individuals in accordance with applicable federal, state, and local laws.
 
 
 If you believe you need an accommodation, please visit our website for additional information.
</div>

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